Thermal conductivity model for nanofiber networks
Zhao, Xinpeng; Huang, Congliang; Liu, Qingkun; Smalyukh, Ivan I.; Yang, Ronggui
2018-02-01
Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.
Thermal conductivity model for nanofiber networks
Energy Technology Data Exchange (ETDEWEB)
Zhao, Xinpeng [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; Huang, Congliang [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China; Liu, Qingkun [Department of Physics, University of Colorado, Boulder, Colorado 80309, USA; Smalyukh, Ivan I. [Department of Physics, University of Colorado, Boulder, Colorado 80309, USA; Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, USA; Yang, Ronggui [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, USA; Buildings and Thermal Systems Center, National Renewable Energy Laboratory, Golden, Colorado 80401, USA
2018-02-28
Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.
Directory of Open Access Journals (Sweden)
Masaru Ishizuka
2011-01-01
Full Text Available In recent years, there is a growing demand to have smaller and lighter electronic circuits which have greater complexity, multifunctionality, and reliability. High-density multichip packaging technology has been used in order to meet these requirements. The higher the density scale is, the larger the power dissipation per unit area becomes. Therefore, in the designing process, it has become very important to carry out the thermal analysis. However, the heat transport model in multichip modules is very complex, and its treatment is tedious and time consuming. This paper describes an application of the thermal network method to the transient thermal analysis of multichip modules and proposes a simple model for the thermal analysis of multichip modules as a preliminary thermal design tool. On the basis of the result of transient thermal analysis, the validity of the thermal network method and the simple thermal analysis model is confirmed.
Leśko, Michał; Bujalski, Wojciech
2017-12-01
The aim of this document is to present the topic of modeling district heating systems in order to enable optimization of their operation, with special focus on thermal energy storage in the pipelines. Two mathematical models for simulation of transient behavior of district heating networks have been described, and their results have been compared in a case study. The operational optimization in a DH system, especially if this system is supplied from a combined heat and power plant, is a difficult and complicated task. Finding a global financial optimum requires considering long periods of time and including thermal energy storage possibilities into consideration. One of the most interesting options for thermal energy storage is utilization of thermal inertia of the network itself. This approach requires no additional investment, while providing significant possibilities for heat load shifting. It is not feasible to use full topological models of the networks, comprising thousands of substations and network sections, for the purpose of operational optimization with thermal energy storage, because such models require long calculation times. In order to optimize planned thermal energy storage actions, it is necessary to model the transient behavior of the network in a very simple way - allowing for fast and reliable calculations. Two approaches to building such models have been presented. Both have been tested by comparing the results of simulation of the behavior of the same network. The characteristic features, advantages and disadvantages of both kinds of models have been identified. The results can prove useful for district heating system operators in the near future.
Probabilistic modeling of crack networks in thermal fatigue
International Nuclear Information System (INIS)
Malesys, N.
2007-11-01
Thermal superficial crack networks have been detected in mixing zone of cooling system in nuclear power plants. Numerous experimental works have already been led to characterize initiation and propagation of these cracks. The random aspect of initiation led to propose a probabilistic model for the formation and propagation of crack networks in thermal fatigue. In a first part, uniaxial mechanical test were performed on smooth and slightly notched specimens in order to characterize the initiation of multiple cracks, their arrest due to obscuration and the coalescence phenomenon by recovery of amplification stress zones. In a second time, the probabilistic model was established under two assumptions: the continuous cracks initiation on surface, described by a Poisson point process law with threshold, and the shielding phenomenon which prohibits the initiation or the propagation of a crack if this one is in the relaxation stress zone of another existing crack. The crack propagation is assumed to follow a Paris' law based on the computation of stress intensity factors at the top and the bottom of crack. The evolution of multiaxial cracks on the surface can be followed thanks to three quantities: the shielding probability, comparable to a damage variable of the structure, the initiated crack density, representing the total number of cracks per unit surface which can be compared to experimental observations, and the propagating crack density, representing the number per unit surface of active cracks in the network. The crack sizes distribution is also computed by the model allowing an easier comparison with experimental results. (author)
Bayesian networks modeling for thermal error of numerical control machine tools
Institute of Scientific and Technical Information of China (English)
Xin-hua YAO; Jian-zhong FU; Zi-chen CHEN
2008-01-01
The interaction between the heat source location,its intensity,thermal expansion coefficient,the machine system configuration and the running environment creates complex thermal behavior of a machine tool,and also makes thermal error prediction difficult.To address this issue,a novel prediction method for machine tool thermal error based on Bayesian networks (BNs) was presented.The method described causal relationships of factors inducing thermal deformation by graph theory and estimated the thermal error by Bayesian statistical techniques.Due to the effective combination of domain knowledge and sampled data,the BN method could adapt to the change of running state of machine,and obtain satisfactory prediction accuracy.Ex-periments on spindle thermal deformation were conducted to evaluate the modeling performance.Experimental results indicate that the BN method performs far better than the least squares(LS)analysis in terms of modeling estimation accuracy.
Electrical equivalent thermal network for direct contact membrane distillation modeling and analysis
Karam, Ayman M.
2016-09-19
Membrane distillation (MD) is an emerging water desalination technology that offers several advantages compared to conventional desalination methods. Although progress has been made to model the physics of the process, there are two common limitations of existing models. Firstly, many of the models are based on the steady-state analysis of the process and secondly, some of the models are based on partial differential equations, which when discretized introduce many states which are not accessible in practice. This paper presents the derivation of a novel dynamic model, based on the analogy between electrical and thermal systems, for direct contact membrane distillation (DCMD). An analogous electrical thermal network is constructed and its elements are parameterized such that the response of the network models the DCMD process. The proposed model captures the spatial and temporal responses of the temperature distribution along the flow direction and is able to accurately predict the distilled water flux output. To demonstrate the adequacy of the proposed model, validation with time varying and steady-state experimental data is presented. (C) 2016 Elsevier Ltd. All rights reserved.
Global thermal analysis of air-air cooled motor based on thermal network
Hu, Tian; Leng, Xue; Shen, Li; Liu, Haidong
2018-02-01
The air-air cooled motors with high efficiency, large starting torque, strong overload capacity, low noise, small vibration and other characteristics, are widely used in different department of national industry, but its cooling structure is complex, it requires the motor thermal management technology should be high. The thermal network method is a common method to calculate the temperature field of the motor, it has the advantages of small computation time and short time consuming, it can save a lot of time in the initial design phase of the motor. The domain analysis of air-air cooled motor and its cooler was based on thermal network method, the combined thermal network model was based, the main components of motor internal and external cooler temperature were calculated and analyzed, and the temperature rise test results were compared to verify the correctness of the combined thermal network model, the calculation method can satisfy the need of engineering design, and provide a reference for the initial and optimum design of the motor.
A Network Model for the Effective Thermal Conductivity of Rigid Fibrous Refractory Insulations
Marschall, Jochen; Cooper, D. M. (Technical Monitor)
1995-01-01
A procedure is described for computing the effective thermal conductivity of a rigid fibrous refractory insulation. The insulation is modeled as a 3-dimensional Cartesian network of thermal conductance. The values and volume distributions of the conductance are assigned to reflect the physical properties of the insulation, its constituent fibers, and any permeating gas. The effective thermal conductivity is computed by considering the simultaneous energy transport by solid conduction, gas conduction and radiation through a cubic volume of model insulation; thus the coupling between heat transfer modes is retained (within the simplifications inherent to the model), rather than suppressed by treating these heat transfer modes as independent. The model takes into account insulation composition, density and fiber anisotropy, as well as the geometric and material properties of the constituent fibers. A relatively good agreement, between calculated and experimentally derived thermal conductivity values, is obtained for a variety of rigid fibrous insulations.
Energy Technology Data Exchange (ETDEWEB)
Huang, Hai; Plummer, Mitchell; Podgorney, Robert
2013-02-01
Advancement of EGS requires improved prediction of fracture development and growth during reservoir stimulation and long-term operation. This, in turn, requires better understanding of the dynamics of the strongly coupled thermo-hydro-mechanical (THM) processes within fractured rocks. We have developed a physically based rock deformation and fracture propagation simulator by using a quasi-static discrete element model (DEM) to model mechanical rock deformation and fracture propagation induced by thermal stress and fluid pressure changes. We also developed a network model to simulate fluid flow and heat transport in both fractures and porous rock. In this paper, we describe results of simulations in which the DEM model and network flow & heat transport model are coupled together to provide realistic simulation of the changes of apertures and permeability of fractures and fracture networks induced by thermal cooling and fluid pressure changes within fractures. Various processes, such as Stokes flow in low velocity pores, convection-dominated heat transport in fractures, heat exchange between fluid-filled fractures and solid rock, heat conduction through low-permeability matrices and associated mechanical deformations are all incorporated into the coupled model. The effects of confining stresses, developing thermal stress and injection pressure on the permeability evolution of fracture and fracture networks are systematically investigated. Results are summarized in terms of implications for the development and evolution of fracture distribution during hydrofracturing and thermal stimulation for EGS.
Evaluation of thermal network correction program using test temperature data
Ishimoto, T.; Fink, L. C.
1972-01-01
An evaluation process to determine the accuracy of a computer program for thermal network correction is discussed. The evaluation is required since factors such as inaccuracies of temperatures, insufficient number of temperature points over a specified time period, lack of one-to-one correlation between temperature sensor and nodal locations, and incomplete temperature measurements are not present in the computer-generated information. The mathematical models used in the evaluation are those that describe a physical system composed of both a conventional and a heat pipe platform. A description of the models used, the results of the evaluation of the thermal network correction, and input instructions for the thermal network correction program are presented.
Fluid temperatures: Modeling the thermal regime of a river network
Rhonda Mazza; Ashley Steel
2017-01-01
Water temperature drives the complex food web of a river network. Aquatic organisms hatch, feed, and reproduce in thermal niches within the tributaries and mainstem that comprise the river network. Changes in water temperature can synchronize or asynchronize the timing of their life stages throughout the year. The water temperature fluctuates over time and place,...
Energy Technology Data Exchange (ETDEWEB)
Chung, Ji Bum [Institute for Advanced Engineering, Yongin (Korea, Republic of); Park, Jong Woon [Korea Electric Power Research Institute, Taejon (Korea, Republic of)
1998-12-31
In order to enhance the dynamic and interactive simulation capability of a system thermal hydraulic code for nuclear power plant, applicability of flow network models in SINDA/FLUINT{sup TM} has been tested by modeling feedwater system and coupling to DSNP which is one of a system thermal hydraulic simulation code for a pressurized heavy water reactor. The feedwater system is selected since it is one of the most important balance of plant systems with a potential to greatly affect the behavior of nuclear steam supply system. The flow network model of this feedwater system consists of condenser, condensate pumps, low and high pressure heaters, deaerator, feedwater pumps, and control valves. This complicated flow network is modeled and coupled to DSNP and it is tested for several normal and abnormal transient conditions such turbine load maneuvering, turbine trip, and loss of class IV power. The results show reasonable behavior of the coupled code and also gives a good dynamic and interactive simulation capabilities for the several mild transient conditions. It has been found that coupling system thermal hydraulic code with a flow network code is a proper way of upgrading simulation capability of DSNP to mature nuclear plant analyzer (NPA). 5 refs., 10 figs. (Author)
Directory of Open Access Journals (Sweden)
Jixin Wang
2014-06-01
Full Text Available This paper presents a rational prediction of temperature field on the differential hybrid system (DHS based on the thermal network method (TNM. The whole thermal network model is built by considering both the contact thermal resistance between gasket and planet gear and the temperature effect on the physical property parameters of lubricant. The contact thermal resistance is obtained by using the concept of contact branch thermal resistance and G-W elastic model. By building an elaborate thermal network model and computing models for power losses and thermal resistances between components, the whole temperature field of DHS under typical operating condition is predicted. Results show that thermal network method can be effectively used to predict the temperature distribution and the rule of temperature variation, the surface roughness significantly affects contact thermal conduction, and the decrease in the thermal resistance of the natural convection between air and DHS housing can effectively improve the thermal environment of DHS.
House thermal model parameter estimation method for Model Predictive Control applications
van Leeuwen, Richard Pieter; de Wit, J.B.; Fink, J.; Smit, Gerardus Johannes Maria
In this paper we investigate thermal network models with different model orders applied to various Dutch low-energy house types with high and low interior thermal mass and containing floor heating. Parameter estimations are performed by using data from TRNSYS simulations. The paper discusses results
Directory of Open Access Journals (Sweden)
Gosukonda Ramana
2017-06-01
Full Text Available Artificial neural networks (ANN and traditional regression models were developed for prediction of thermal properties of sweet sorghum bagasse as a function of moisture content and room temperature. Predictions were made for three thermal properties: 1 thermal conductivity, 2 volumetric specific heat, and 3 thermal diffusivity. Each thermal property had five levels of moisture content (8.52%, 12.93%, 18.94%, 24.63%, and 28.62%, w. b. and room temperature as inputs. Data were sub-partitioned for training, testing, and validation of models. Backpropagation (BP and Kalman Filter (KF learning algorithms were employed to develop nonparametric models between input and output data sets. Statistical indices including correlation coefficient (R between actual and predicted outputs were produced for selecting the suitable models. Prediction plots for thermal properties indicated that the ANN models had better accuracy from unseen patterns as compared to regression models. In general, ANN models were able to strongly generalize and interpolate unseen patterns within the domain of training.
Thermal Runaway in Jammed Networks
Lechman, Jeremy; Yarrington, Cole; Bolintineanu, Dan
2017-06-01
The study of thermal explosion has a long history. Names such as Semenov and Frank-Kamenetskii are associated with classical model descriptions under particular assumptions. In this talk we revisit this problem with particular focus on the latter's model for conduction dominated thermal transport and Arrenhius-type reaction chemistry. We extend this description to the case of inhomogeneous microstructure generated by packing mono-sized spheres via a well-defined ``Jamming'' protocol. With these material structures in hand, we recast the Frank-Kamenetskii problem into a reduced-order network form for conduction in particle packs. With this model we can efficiently investigate the variability of the time to ignition due to the random microstructure. Additionally, we propose a modal decomposition and stability analysis of the model akin to stability of linear systems. We highlight the physical insights this approach can give with respect to questions of material dependent performance variability. Sandia National Laboratories is a multiprogram laboratory managed and operated by Sandia Corporation, a Lockheed-Martin Company, for the U. S. Department of Energy's National Nuclear Security Administration under Contract No. DE-AC04-94AL85000.
A 3D Lumped Thermal Network Model for Long-term Load Profiles Analysis in High Power IGBT Modules
DEFF Research Database (Denmark)
Bahman, Amir Sajjad; Ma, Ke; Ghimire, Pramod
2016-01-01
)-based simulation is another method which is often used to analyze the steady-state thermal distribution of IGBT modules, but it is not possible to be used for long-term analysis of load profiles of power converter, which is needed for reliability assessments and better thermal design. This paper proposes a novel...... enables both accurate and fast temperature estimation of high power IGBT modules in the real loading conditions of the converter; meanwhile the critical details of the thermal dynamics and thermal distribution are also maintained. The proposed thermal model is verified by both FEM simulation......The conventional RC lumped thermal networks are widely used to estimate the temperature of power devices, but they are lack of accuracy in addressing detailed thermal behaviors/couplings in different locations and layers of the high power IGBT modules. On the other hand, Finite Element (FE...
International Nuclear Information System (INIS)
Moon, Jin Woo; Jung, Sung Kwon
2016-01-01
Highlights: • An ANN model for predicting optimal start moment of the cooling system was developed. • An ANN model for predicting the amount of cooling energy consumption was developed. • An optimal control algorithm was developed employing two ANN models. • The algorithm showed the advanced thermal comfort and energy efficiency. - Abstract: The aim of this study was to develop a control algorithm to demonstrate the improved thermal comfort and building energy efficiency of accommodation buildings in the cooling season. For this, two artificial neural network (ANN)-based predictive and adaptive models were developed and employed in the algorithm. One model predicted the cooling energy consumption during the unoccupied period for different setback temperatures and the other predicted the time required for restoring current indoor temperature to the normal set-point temperature. Using numerical simulation methods, the prediction accuracy of the two ANN models and the performance of the algorithm were tested. Through the test result analysis, the two ANN models showed their prediction accuracy with an acceptable error rate when applied in the control algorithm. In addition, the two ANN models based algorithm can be used to provide a more comfortable and energy efficient indoor thermal environment than the two conventional control methods, which respectively employed a fixed set-point temperature for the entire day and a setback temperature during the unoccupied period. Therefore, the operating range was 23–26 °C during the occupied period and 25–28 °C during the unoccupied period. Based on the analysis, it can be concluded that the optimal algorithm with two predictive and adaptive ANN models can be used to design a more comfortable and energy efficient indoor thermal environment for accommodation buildings in a comprehensive manner.
Thermal photovoltaic solar integrated system analysis using neural networks
Energy Technology Data Exchange (ETDEWEB)
Ashhab, S. [Hashemite Univ., Zarqa (Jordan). Dept. of Mechanical Engineering
2007-07-01
The energy demand in Jordan is primarily met by petroleum products. As such, the development of renewable energy systems is quite attractive. In particular, solar energy is a promising renewable energy source in Jordan and has been used for food canning, paper production, air-conditioning and sterilization. Artificial neural networks (ANNs) have received significant attention due to their capabilities in forecasting, modelling of complex nonlinear systems and control. ANNs have been used for forecasting solar energy. This paper presented a study that examined a thermal photovoltaic solar integrated system that was built in Jordan. Historical input-output system data that was collected experimentally was used to train an ANN that predicted the collector, PV module, pump and total efficiencies. The model predicted the efficiencies well and can therefore be utilized to find the operating conditions of the system that will produce the maximum system efficiencies. The paper provided a description of the photovoltaic solar system including equations for PV module efficiency; pump efficiency; and total efficiency. The paper also presented data relevant to the system performance and neural networks. The results of a neural net model were also presented based on the thermal PV solar integrated system data that was collected. It was concluded that the neural net model of the thermal photovoltaic solar integrated system set the background for achieving the best system performance. 10 refs., 6 figs.
Dynamic thermo-hydraulic model of district cooling networks
International Nuclear Information System (INIS)
Oppelt, Thomas; Urbaneck, Thorsten; Gross, Ulrich; Platzer, Bernd
2016-01-01
Highlights: • A dynamic thermo-hydraulic model for district cooling networks is presented. • The thermal modelling is based on water segment tracking (Lagrangian approach). • Thus, numerical errors and balance inaccuracies are avoided. • Verification and validation studies proved the reliability of the model. - Abstract: In the present paper, the dynamic thermo-hydraulic model ISENA is presented which can be applied for answering different questions occurring in design and operation of district cooling networks—e.g. related to economic and energy efficiency. The network model consists of a quasistatic hydraulic model and a transient thermal model based on tracking water segments through the whole network (Lagrangian method). Applying this approach, numerical errors and balance inaccuracies can be avoided which leads to a higher quality of results compared to other network models. Verification and validation calculations are presented in order to show that ISENA provides reliable results and is suitable for practical application.
On-line thermal margin estimation of a PWR core using a neural network approach
International Nuclear Information System (INIS)
Park, Soon Ok; Kim, Hyun Koon; Lee, Seung Hynk; Chang, Soon Heung
1992-01-01
A new approach for on-line thermal margin monitoring of a PWR Core is proposed in this paper, where a neural network model is introduced to predict the DNBR values at the given reactor operating conditions. The neural network is learned by the Back Propagation algorithm with the optimized random training data and is tested to investigate the generalized performance for the steady state operating region as well as for the transient situations where DNB is of the primary concern. The test results show that the high level of accuracy in predicting the DNBR can be achieved by the neural network model compared to the detailed code results. An insight has been gained from this study that the neural network model for estimating DNB performance can be a viable tool for on-line thermal margin monitoring of a nuclear power plant
Parameter estimation of breast tumour using dynamic neural network from thermal pattern
Directory of Open Access Journals (Sweden)
Elham Saniei
2016-11-01
Full Text Available This article presents a new approach for estimating the depth, size, and metabolic heat generation rate of a tumour. For this purpose, the surface temperature distribution of a breast thermal image and the dynamic neural network was used. The research consisted of two steps: forward and inverse. For the forward section, a finite element model was created. The Pennes bio-heat equation was solved to find surface and depth temperature distributions. Data from the analysis, then, were used to train the dynamic neural network model (DNN. Results from the DNN training/testing confirmed those of the finite element model. For the inverse section, the trained neural network was applied to estimate the depth temperature distribution (tumour position from the surface temperature profile, extracted from the thermal image. Finally, tumour parameters were obtained from the depth temperature distribution. Experimental findings (20 patients were promising in terms of the model’s potential for retrieving tumour parameters.
Multi-Node Thermal System Model for Lithium-Ion Battery Packs: Preprint
Energy Technology Data Exchange (ETDEWEB)
Shi, Ying; Smith, Kandler; Wood, Eric; Pesaran, Ahmad
2015-09-14
Temperature is one of the main factors that controls the degradation in lithium ion batteries. Accurate knowledge and control of cell temperatures in a pack helps the battery management system (BMS) to maximize cell utilization and ensure pack safety and service life. In a pack with arrays of cells, a cells temperature is not only affected by its own thermal characteristics but also by its neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model, which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs. neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model, which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs.
International Nuclear Information System (INIS)
Kim, Hyun Koon
1992-02-01
One of the key safety parameters related to thermal margin in a Pressurized Water Reactor (PWR) core, is Departure from Nucleate Boiling Ratio (DNBR), which is to be assessed and continuously monitored during operation via either an analog or a digital monitoring system. The digital monitoring system, in general, allows more thermal margin than the analog system through the on-line computation of DNBR using the measured parameters as inputs to a simplified, fast running computer code. The purpose of this thesis is to develop an advanced method for on-line DNBR estimation by introducing an artifactual neural network model for best-estimation of DNBR at the given reactor operating conditions. the neural network model, consisting of three layers with five operating parameters in the input layer, provides real-time prediction accuracy of DNBR by training the network against the detailed simulation results for various operating conditions. The overall training procedure is developed to learn the characteristics of DNBR behaviour in the reactor core. First, a set of random combination of input variables is generated by Latin Hypercube Sampling technique performed on a wide range of input parameters. Second, the target values of DNBR to be referenced for training are calculated using a detailed simulation code, COBRA-IV. Third, the optimized training input data are selected. Then, training is performed using an Error Back Propagation algorithm. After completion of training, the network is tested on the examining data set in order to investigate the generalization capability of the network responses for the steady state operating condition as well as for the transient situations where DNB is of a primary concern. The test results show that the values of DNBR predicted by the neural network are maintained at a high level of accuracy for the steady state condition, and are in good agreements with the transient situation, although slightly conservative as compared to those
Implementing network constraints in the EMPS model
Energy Technology Data Exchange (ETDEWEB)
Helseth, Arild; Warland, Geir; Mo, Birger; Fosso, Olav B.
2010-02-15
This report concerns the coupling of detailed market and network models for long-term hydro-thermal scheduling. Currently, the EPF model (Samlast) is the only tool available for this task for actors in the Nordic market. A new prototype for solving the coupled market and network problem has been developed. The prototype is based on the EMPS model (Samkjoeringsmodellen). Results from the market model are distributed to a detailed network model, where a DC load flow detects if there are overloads on monitored lines or intersections. In case of overloads, network constraints are generated and added to the market problem. Theoretical and implementation details for the new prototype are elaborated in this report. The performance of the prototype is tested against the EPF model on a 20-area Nordic dataset. (Author)
Thermal behavior of poly(2-hydroxyethyl methacrylate-bis-[trimethoxysilylpropyl]amine) networks
International Nuclear Information System (INIS)
Bustos Figueroa, L A; Salgado Delgado, R; García Hernandez, E; Vargas Galarza, Z; Rubio Rosas, E; Salgado Rodriguez, R
2013-01-01
Poly(HEMA-BisSi) networks were prepared by using acid-catalyzed sol-gel of bis-[trimethoxysilylpropyl]amine (BisSi) and free radical polymerization of 2-hydroxyethyl methacrylate (HEMA). The thermal properties of the poly(HEMA-BisSi) networks were investigated with differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). The thermal behavior of these networks was also compared with homopolymers (The networks formed in both PHEMA and PBisSi gels were identified). The glass transition temperature (T g ) of PHEMA homopolymer was found as 103.74 °C. The thermal degradation of the poly(HEMA-BisSi) networks with different silica contents (e.g. 10, 15 and 25 wt%) were evaluated with use of DTG. It was observed that the thermal degradation temperature of poly(HEMA-BisSi) networks changed much with the BisSi content.
Real time thermal hydraulic model for high temperature gas-cooled reactor core
International Nuclear Information System (INIS)
Sui Zhe; Sun Jun; Ma Yuanle; Zhang Ruipeng
2013-01-01
A real-time thermal hydraulic model of the reactor core was described and integrated into the simulation system for the high temperature gas-cooled pebble bed reactor nuclear power plant, which was developed in the vPower platform, a new simulation environment for nuclear and fossil power plants. In the thermal hydraulic model, the helium flow paths were established by the flow network tools in order to obtain the flow rates and pressure distributions. Meanwhile, the heat structures, representing all the solid heat transfer elements in the pebble bed, graphite reflectors and carbon bricks, were connected by the heat transfer network in order to solve the temperature distributions in the reactor core. The flow network and heat transfer network were coupled and calculated in real time. Two steady states (100% and 50% full power) and two transients (inlet temperature step and flow step) were tested that the quantitative comparisons of the steady results with design data and qualitative analysis of the transients showed the good applicability of the present thermal hydraulic model. (authors)
A candidate multimodal functional genetic network for thermal adaptation
Directory of Open Access Journals (Sweden)
Katharina C. Wollenberg Valero
2014-09-01
Full Text Available Vertebrate ectotherms such as reptiles provide ideal organisms for the study of adaptation to environmental thermal change. Comparative genomic and exomic studies can recover markers that diverge between warm and cold adapted lineages, but the genes that are functionally related to thermal adaptation may be difficult to identify. We here used a bioinformatics genome-mining approach to predict and identify functions for suitable candidate markers for thermal adaptation in the chicken. We first established a framework of candidate functions for such markers, and then compiled the literature on genes known to adapt to the thermal environment in different lineages of vertebrates. We then identified them in the genomes of human, chicken, and the lizard Anolis carolinensis, and established a functional genetic interaction network in the chicken. Surprisingly, markers initially identified from diverse lineages of vertebrates such as human and fish were all in close functional relationship with each other and more associated than expected by chance. This indicates that the general genetic functional network for thermoregulation and/or thermal adaptation to the environment might be regulated via similar evolutionarily conserved pathways in different vertebrate lineages. We were able to identify seven functions that were statistically overrepresented in this network, corresponding to four of our originally predicted functions plus three unpredicted functions. We describe this network as multimodal: central regulator genes with the function of relaying thermal signal (1, affect genes with different cellular functions, namely (2 lipoprotein metabolism, (3 membrane channels, (4 stress response, (5 response to oxidative stress, (6 muscle contraction and relaxation, and (7 vasodilation, vasoconstriction and regulation of blood pressure. This network constitutes a novel resource for the study of thermal adaptation in the closely related nonavian reptiles and
Multiscale Modeling of UHTC: Thermal Conductivity
Lawson, John W.; Murry, Daw; Squire, Thomas; Bauschlicher, Charles W.
2012-01-01
We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.
Energy Technology Data Exchange (ETDEWEB)
Kurt, Hueseyin; Atik, Kemal; Oezkaymak, Mehmet; Recebli, Ziyaddin [Zonguldak Karaelmas University, Karabuk Technical Education Faculty, 78200 Karabuk (Turkey)
2008-02-15
Work to date has shown that Artificial Neural Network (ANN) has not been used for predicting thermal performance parameters of a solar cooker. The objective of this study is to predict thermal performance parameters such as absorber plate, enclosure air and pot water temperatures of the experimentally investigated box type solar cooker by using the ANN. Data set is obtained from the box type solar cooker which was tested under various experimental conditions. A feed-forward neural network based on back propagation algorithm was developed to predict the thermal performance of solar cooker with and without reflector. Mathematical formulations derived from the ANN model are presented for each predicting temperatures. The experimental data set consists of 126 values. These were divided into two groups, of which the 96 values were used for training/learning of the network and the rest of the data (30 values) for testing/validation of the network performance. The performance of the ANN predictions was evaluated by comparing the prediction results with the experimental results. The results showed a good regression analysis with the correlation coefficients in the range of 0.9950-0.9987 and mean relative errors (MREs) in the range of 3.925-7.040% for the test data set. The regression coefficients indicated that the ANN model can successfully be used for the prediction of the thermal performance parameters of a box type solar cooker with a high degree of accuracy. (author)
Simulation of thermal-hydraulic process in reactor of HTR-PM based on flow and heat transfer network
International Nuclear Information System (INIS)
Zhou Kefeng; Zhou Yangping; Sui Zhe; Ma Yuanle
2012-01-01
The development of HTR-PM full scale simulator (FSS) is an important part in the project. The simulation of thermal-hydraulic process in reactor is one of the key technologies in the development of FSS. The simulation of thermal-hydraulic process in reactor was studied. According to the geometry structures and the characteristics of thermal-hydraulic process in reactor, the model was setup in components construction way. Based on the established simulation method of flow and heat transfer network, a Fortran code was developed and the simulation of thermal-hydraulic process was achieved. The simulation results of 50% FP steady state, 100% FP steady state and control rod mistakenly ascension accidents were given. The verification of simulation results was carried out by comparing with the design and analysis code THERMIX. The results show that the method and model based on flow and heat transfer network can meet the requirements of FSS and reflect the features of thermal-hydraulic process in HTR-PM. (authors)
Directory of Open Access Journals (Sweden)
Yuan-Chieh Lo
2018-02-01
Full Text Available Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe. Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t| °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR technique and implemented into the real-time embedded system.
Study of Error Propagation in the Transformations of Dynamic Thermal Models of Buildings
Directory of Open Access Journals (Sweden)
Loïc Raillon
2017-01-01
Full Text Available Dynamic behaviour of a system may be described by models with different forms: thermal (RC networks, state-space representations, transfer functions, and ARX models. These models, which describe the same process, are used in the design, simulation, optimal predictive control, parameter identification, fault detection and diagnosis, and so on. Since more forms are available, it is interesting to know which one is the most suitable by estimating the sensitivity of the model to transform into a physical model, which is represented by a thermal network. A procedure for the study of error by Monte Carlo simulation and of factor prioritization is exemplified on a simple, but representative, thermal model of a building. The analysis of the propagation of errors and of the influence of the errors on the parameter estimation shows that the transformation from state-space representation to transfer function is more robust than the other way around. Therefore, if only one model is chosen, the state-space representation is preferable.
International Nuclear Information System (INIS)
Carlson, K.E.; Ransom, V.H.; Roth, P.A.
1987-03-01
The ATHENA (Advanced Thermal Hydraulic Energy Network Analyzer) code has been developed to perform transient simulation of the thermal hydraulic systems that may be found in fusion reactors, space reactors, and other advanced systems. As an assessment of current capability the code was applied to a number of physical problems, both conceptual and actual experiments. Results indicate that the numerical solution to the basic conservation equations is technically sound, and that generally good agreement can be obtained when modeling relevant hydrodynamic experiments. The assessment also demonstrates basic fusion system modeling capability and verifies compatibility of the code with both CDC and CRAY mainframes. Areas where improvements could be made include constitutive modeling, which describes the interfacial exchange term. 13 refs., 84 figs
International Nuclear Information System (INIS)
Tveit, Tor-Martin; Savola, Tuula; Gebremedhin, Alemayehu; Fogelholm, Carl-Johan
2009-01-01
By using thermal storages it is possible to decouple the generation of power and heat, and it can also lead to an reduction in investments, as the storage can be used to cover the peak load periods. This work presents a MINLP model that can be used for analysing new investments and the long-term operation of CHP plants in a district heating network with long-term thermal storage. The model presented in this work includes the non-linear off-design behaviour of the CHP plants as well as a generic mathematical model of the thermal storage, without the need to fix temperatures and pressure. The model is formulated in such a way that it is suitable for deterministic MINLP solvers. The model is non-convex, and subsequently global optimality cannot be guaranteed with local solvers. In order to reduce the chance of obtaining a poor local optimum compared to the global optimum, the model should be solved many times with the initial values varying randomly. It is possible to extract a lot of results from the model, for instance total annual profit, the optimal selection of process options, mass flow through the plant, and generated power from each plant. The formulation of the model makes it suitable for deterministic MINLP solvers
Dynamic electro-thermal modeling of all-vanadium redox flow battery with forced cooling strategies
International Nuclear Information System (INIS)
Wei, Zhongbao; Zhao, Jiyun; Xiong, Binyu
2014-01-01
Highlights: • A dynamic electro-thermal model is proposed for VRB with forced cooling. • The Foster network is adopted to model the battery cooling process. • Both the electrolyte temperature and terminal voltage can be accurately predicted. • The flow rate of electrolyte and coolant significantly impact battery performance. - Abstract: The present study focuses on the dynamic electro-thermal modeling for the all-vanadium redox flow battery (VRB) with forced cooling strategies. The Foster network is adopted to dynamically model the heat dissipation of VRB with heat exchangers. The parameters of Foster network are extracted by fitting the step response of it to the results of linearized CFD model. Then a complete electro-thermal model is proposed by coupling the heat generation model, Foster network and electrical model. Results show that the established model has nearly the same accuracy with the nonlinear CFD model in electrolyte temperature prediction but drastically improves the computational efficiency. The modeled terminal voltage is also benchmarked with the experimental data under different current densities. The electrolyte temperature is found to be significantly influenced by the flow rate of coolant. As compared, although the electrolyte flow rate has unremarkable impact on electrolyte temperature, its effect on system pressure drop and battery efficiency is significant. Increasing the electrolyte flow rate improves the coulombic efficiency, voltage efficiency and energy efficiency simultaneously but at the expense of higher pump power demanded. An optimal flow rate exists for each operating condition to maximize the system efficiency
Applications of artificial neural networks for thermal analysis of heat exchangers - A review
International Nuclear Information System (INIS)
Mohanraj, M.; Jayaraj, S.; Muraleedharan, C.
2015-01-01
Artificial neural networks (ANN) have been widely used for thermal analysis of heat exchangers during the last two decades. In this paper, the applications of ANN for thermal analysis of heat exchangers are reviewed. The reported investigations on thermal analysis of heat exchangers are categorized into four major groups, namely (i) modeling of heat exchangers, (ii) estimation of heat exchanger parameters, (iii) estimation of phase change characteristics in heat exchangers and (iv) control of heat exchangers. Most of the papers related to the applications of ANN for thermal analysis of heat exchangers are discussed. The limitations of ANN for thermal analysis of heat exchangers and its further research needs in this field are highlighted. ANN is gaining popularity as a tool, which can be successfully used for the thermal analysis of heat exchangers with acceptable accuracy. (authors)
Directory of Open Access Journals (Sweden)
Hong Yang
2015-07-01
Full Text Available Thermally modified wood has high dimensional stability and biological durability.But if the process parameters of thermal modification are not appropriate, then there will be a decline in the physical properties of wood.A neural network algorithm was employed in this study to establish the relationship between the process parameters of high-temperature and high-pressure thermal modification and the mechanical properties of the wood. Three important parameters: temperature, relative humidity, and treatment time, were considered as the inputs to the neural network. Back propagation (BP neural network and radial basis function (RBF neural network models for prediction were built and compared. The comparison showed that the RBF neural network model had advantages in network structure, convergence speed, and generalization capacity. On this basis, the inverse model, reflecting the relationship between the process parameters and the mechanical properties of wood, was established. Given the desired mechanical properties of the wood, the thermal modification process parameters could be inversely optimized and predicted. The results indicated that the model has good learning ability and generalization capacity. This is of great importance for the theoretical and applicational studies of the thermal modification of wood.
Directory of Open Access Journals (Sweden)
Khalid Ahmed Joudi
2017-01-01
Full Text Available This paper presents a computer simulation model of a thermally activated roof (TAR to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time dependent with the variation of the ambient wet bulb temperature. Results from RC-thermal modeling were compared with experimental measurements for a second story room measuring 5.5 m x 4 m x 3 m at Amarah city/ Iraq (31.865 ˚N, 47.128 ˚E for 21 July, 2013. The roof was constructed of 200 mm concrete slab, 150 mm turf and 50 mm insulation. Galvanized 13 mm steel pipe coils were buried in the roof slab with a pipe occupation ratio of 0.12. The walls were constructed of 240 mm common brick with 10mm cement plaster on the inside and outside surfaces and 20 mm Styrofoam insulation on the inside surface and covered with PVC panel. Thermistors were used to measure the indoor and outdoor temperatures, TAR system water inlet and outlet temperatures and temperature distribution inside the concrete slab. The effect of pipe spacing and water mass flow rate were evaluated. Agreement was good between the experimental and RC-thermal model. Concrete core temperature reaches the supply water temperature faster for lower pipe spacing. Heat extracted from the space increased with water mass flow rate to an optimum of 0.0088 kg/s.m².
Orion Active Thermal Control System Dynamic Modeling Using Simulink/MATLAB
Wang, Xiao-Yen J.; Yuko, James
2010-01-01
This paper presents dynamic modeling of the crew exploration vehicle (Orion) active thermal control system (ATCS) using Simulink (Simulink, developed by The MathWorks). The model includes major components in ATCS, such as heat exchangers and radiator panels. The mathematical models of the heat exchanger and radiator are described first. Four different orbits were used to validate the radiator model. The current model results were compared with an independent Thermal Desktop (TD) (Thermal Desktop, PC/CAD-based thermal model builder, developed in Cullimore & Ring (C&R) Technologies) model results and showed good agreement for all orbits. In addition, the Orion ATCS performance was presented for three orbits and the current model results were compared with three sets of solutions- FloCAD (FloCAD, PC/CAD-based thermal/fluid model builder, developed in C&R Technologies) model results, SINDA/FLUINT (SINDA/FLUINT, a generalized thermal/fluid network-style solver ) model results, and independent Simulink model results. For each case, the fluid temperatures at every component on both the crew module and service module sides were plotted and compared. The overall agreement is reasonable for all orbits, with similar behavior and trends for the system. Some discrepancies exist because the control algorithm might vary from model to model. Finally, the ATCS performance for a 45-hr nominal mission timeline was simulated to demonstrate the capability of the model. The results show that the ATCS performs as expected and approximately 2.3 lb water was consumed in the sublimator within the 45 hr timeline before Orion docked at the International Space Station.
Energy Technology Data Exchange (ETDEWEB)
Ahn, S.H., E-mail: k175ash@kins.re.kr [Korea Institute of Nuclear Safety (KINS) (Korea, Republic of); Aksan, N., E-mail: nusr.aksan@gmail.com [University of Pisa San Piero a Grado Nuclear Research Group (GRNSPG) (Italy); Austregesilo, H., E-mail: henrique.austregesilo@grs.de [Gesellschaft für Anlagen- und Reaktorsicherheit (GRS) (Germany); Bestion, D., E-mail: dominique.bestion@cea.fr [Commissariat à l’énergie atomique et aux énergies alternatives (CEA) (France); Chung, B.D., E-mail: bdchung@kaeri.re.kr [Korea Atomic Energy Research Institute (KAERI) (Korea, Republic of); D’Auria, F., E-mail: f.dauria@ing.unipi.it [University of Pisa San Piero a Grado Nuclear Research Group (GRNSPG) (Italy); Emonot, P., E-mail: philippe.emonot@cea.fr [Commissariat à l’énergie atomique et aux énergies alternatives (CEA) (France); Gandrille, J.L., E-mail: jeanluc.gandrille@areva.com [AREVA NP (France); Hanninen, M., E-mail: markku.hanninen@vtt.fi [VTT Technical Research Centre of Finland (VTT) (Finland); Horvatović, I., E-mail: i.horvatovic@ing.unipi.it [University of Pisa San Piero a Grado Nuclear Research Group (GRNSPG) (Italy); Kim, K.D., E-mail: kdkim@kaeri.re.kr [Korea Atomic Energy Research Institute (KAERI) (Korea, Republic of); Kovtonyuk, A., E-mail: a.kovtonyuk@ing.unipi.it [University of Pisa San Piero a Grado Nuclear Research Group (GRNSPG) (Italy); Petruzzi, A., E-mail: a.petruzzi@ing.unipi.it [University of Pisa San Piero a Grado Nuclear Research Group (GRNSPG) (Italy)
2015-01-15
Highlights: • We briefly presented the project called Forum and Network of System Thermal-Hydraulics Codes in Nuclear Reactor Thermal-Hydraulics (FONESYS). • We presented FONESYS participants and their codes. • We explained FONESYS projects motivation, its main targets and working modalities. • We presented FONESYS position about projects topics and subtopics. - Abstract: The purpose of this article is to present briefly the project called Forum and Network of System Thermal-Hydraulics Codes in Nuclear Reactor Thermal-Hydraulics (FONESYS), its participants, the motivation for the project, its main targets and working modalities. System Thermal-Hydraulics (SYS-TH) codes, also as part of the Best Estimate Plus Uncertainty (BEPU) approaches, are expected to achieve a more-and-more relevant role in nuclear reactor technology, safety and design. Namely, the number of code-users can easily be predicted to increase in the countries where nuclear technology is exploited. Thus, the idea of establishing a forum and a network among the code developers and with possible extension to code users has started to have major importance and value. In this framework the FONESYS initiative has been created. The main targets of FONESYS are: • To promote the use of SYS-TH Codes and the application of the BEPU approaches. • To establish acceptable and recognized procedures and thresholds for Verification and Validation (V and V). • To create a common ground for discussing envisaged improvements in various areas, including user-interface, and the connection with other numerical tools, including Computational Fluid Dynamics (CFD) Codes.
Network structure and thermal stability study of high temperature seal glass
Lu, K.; Mahapatra, M. K.
2008-10-01
High temperature seal glass has stringent requirement on glass thermal stability, which is dictated by glass network structures. In this study, a SrO-La2O3-Al2O3-B2O3-SiO2 based glass system was studied using nuclear magnetic resonance, Raman spectroscopy, and x-ray diffraction for solid oxide cell application purpose. Glass structural unit neighboring environment and local ordering were evaluated. Glass network connectivity as well as silicon and boron glass former coordination were calculated for different B2O3:SiO2 ratios. Thermal stability of the borosilicate glasses was studied after thermal treatment at 850 °C. The study shows that high B2O3 content induces BO4 and SiO4 structural unit ordering, increases glass localized inhomogeneity, decreases glass network connectivity, and causes devitrification. Glass modifiers interact with either silicon- or boron-containing structural units and form different devitrified phases at different B2O3:SiO2 ratios. B2O3-free glass shows the best thermal stability among the studied compositions, remaining stable after thermal treatment for 200 h at 850 °C.
Models for thermal and mechanical monitoring of power transformers
Energy Technology Data Exchange (ETDEWEB)
Vilaithong, Rummiya
2011-07-01
At present, for economic reasons, there is an increasing emphasis on keeping transformers in service for longer than in the past. A condition-based maintenance using an online monitoring and diagnostic system is one option to ensure reliability of the transformer operation. The key parameters for effectively monitoring equipment can be selected by failure statistics and estimated failure consequences. In this work, two key aspects of transformer condition monitoring are addressed in depth: thermal behaviour and behaviour of on-load tap changers. In the first part of the work, transformer thermal behaviour is studied, focussing on top-oil temperatures. Through online comparison of a measured value of the top-oil temperature and its calculated value, some rapidly developing failures in power transformers such as malfunction of the cooling unit may be detected. Predictions of top-oil temperature can be obtained by means of a mathematical model. Long-term investigations on some dynamic top-oil temperature models are presented for three different types of transformer units. The last-state top-oil temperature, load current, ambient temperature and the operating state of pumps and fans are applied as inputs of the top-oil temperature models. In the fundamental physical models presented, some constant parameters are required and can be estimated using a least-squares optimization technique. Multilayer Feed-forward and Recurrent neural network models are also proposed and investigated. The neural network models are trained with three different Backpropagation training algorithms: Levenberg-Marquardt, Scaled Conjugate Gradient and Automated Bayesian Regularization. The effect of varying operating conditions of the cooling units and the non-steady-state behaviour of loading conditions, as well as ambient temperature are noted. Results show sophisticated temperature prediction is possible using the neural network models that is generally more accurate than with the physical
Flow distribution analysis on the cooling tube network of ITER thermal shield
International Nuclear Information System (INIS)
Nam, Kwanwoo; Chung, Wooho; Noh, Chang Hyun; Kang, Dong Kwon; Kang, Kyoung-O; Ahn, Hee Jae; Lee, Hyeon Gon
2014-01-01
Thermal shield (TS) is to be installed between the vacuum vessel or the cryostat and the magnets in ITER tokamak to reduce the thermal radiation load to the magnets operating at 4.2K. The TS is cooled by pressurized helium gas at the inlet temperature of 80K. The cooling tube is welded on the TS panel surface and the composed flow network of the TS cooling tubes is complex. The flow rate in each panel should be matched to the thermal design value for effective radiation shielding. This paper presents one dimensional analysis on the flow distribution of cooling tube network for the ITER TS. The hydraulic cooling tube network is modeled by an electrical analogy. Only the cooling tube on the TS surface and its connecting pipe from the manifold are considered in the analysis model. Considering the frictional factor and the local loss in the cooling tube, the hydraulic resistance is expressed as a linear function with respect to mass flow rate. Sub-circuits in the TS are analyzed separately because each circuit is controlled by its own control valve independently. It is found that flow rates in some panels are insufficient compared with the design values. In order to improve the flow distribution, two kinds of design modifications are proposed. The first one is to connect the tubes of the adjacent panels. This will increase the resistance of the tube on the panel where the flow rate is excessive. The other design suggestion is that an orifice is installed at the exit of tube routing where the flow rate is to be reduced. The analysis for the design suggestions shows that the flow mal-distribution is improved significantly
Lo Russo, Stefano; Taddia, Glenda; Verda, Vittorio
2014-05-01
The common use of well doublets for groundwater-sourced heating or cooling results in a thermal plume of colder or warmer re-injected groundwater known as the Thermal Affected Zone(TAZ). The plumes may be regarded either as a potential anthropogenic geothermal resource or as pollution, depending on downstream aquifer usage. A fundamental aspect in groundwater heat pump (GWHP) plant design is the correct evaluation of the thermally affected zone that develops around the injection well. Temperature anomalies are detected through numerical methods. Crucial elements in the process of thermal impact assessment are the sizes of installations, their position, the heating/cooling load of the building, and the temperature drop/increase imposed on the re-injected water flow. For multiple-well schemes, heterogeneous aquifers, or variable heating and cooling loads, numerical models that simulate groundwater and heat transport are needed. These tools should consider numerous scenarios obtained considering different heating/cooling loads, positions, and operating modes. Computational fluid dynamic (CFD) models are widely used in this field because they offer the opportunity to calculate the time evolution of the thermal plume produced by a heat pump, depending on the characteristics of the subsurface and the heat pump. Nevertheless, these models require large computational efforts, and therefore their use may be limited to a reasonable number of scenarios. Neural networks could represent an alternative to CFD for assessing the TAZ under different scenarios referring to a specific site. The use of neural networks is proposed to determine the time evolution of the groundwater temperature downstream of an installation as a function of the possible utilization profiles of the heat pump. The main advantage of neural network modeling is the possibility of evaluating a large number of scenarios in a very short time, which is very useful for the preliminary analysis of future multiple
THERMAL TEXTURE GENERATION AND 3D MODEL RECONSTRUCTION USING SFM AND GAN
Directory of Open Access Journals (Sweden)
V. V. Kniaz
2018-05-01
Full Text Available Realistic 3D models with textures representing thermal emission of the object are widely used in such fields as dynamic scene analysis, autonomous driving, and video surveillance. Structure from Motion (SfM methods provide a robust approach for the generation of textured 3D models in the visible range. Still, automatic generation of 3D models from the infrared imagery is challenging due to an absence of the feature points and low sensor resolution. Recent advances in Generative Adversarial Networks (GAN have proved that they can perform complex image-to-image transformations such as a transformation of day to night and generation of imagery in a different spectral range. In this paper, we propose a novel method for generation of realistic 3D models with thermal textures using the SfM pipeline and GAN. The proposed method uses visible range images as an input. The images are processed in two ways. Firstly, they are used for point matching and dense point cloud generation. Secondly, the images are fed into a GAN that performs the transformation from the visible range to the thermal range. We evaluate the proposed method using real infrared imagery captured with a FLIR ONE PRO camera. We generated a dataset with 2000 pairs of real images captured in thermal and visible range. The dataset is used to train the GAN network and to generate 3D models using SfM. The evaluation of the generated 3D models and infrared textures proved that they are similar to the ground truth model in both thermal emissivity and geometrical shape.
Afrand, Masoud; Hemmat Esfe, Mohammad; Abedini, Ehsan; Teimouri, Hamid
2017-03-01
The current paper first presents an empirical correlation based on experimental results for estimating thermal conductivity enhancement of MgO-water nanofluid using curve fitting method. Then, artificial neural networks (ANNs) with various numbers of neurons have been assessed by considering temperature and MgO volume fraction as the inputs variables and thermal conductivity enhancement as the output variable to select the most appropriate and optimized network. Results indicated that the network with 7 neurons had minimum error. Eventually, the output of artificial neural network was compared with the results of the proposed empirical correlation and those of the experiments. Comparisons revealed that ANN modeling was more accurate than curve-fitting method in the predicting the thermal conductivity enhancement of the nanofluid.
Envisioning, quantifying, and managing thermal regimes on river networks
Steel, E. Ashley; Beechie, Timothy J.; Torgersen, Christian E.; Fullerton, Aimee H.
2017-01-01
Water temperatures fluctuate in time and space, creating diverse thermal regimes on river networks. Temporal variability in these thermal landscapes has important biological and ecological consequences because of nonlinearities in physiological reactions; spatial diversity in thermal landscapes provides aquatic organisms with options to maximize growth and survival. However, human activities and climate change threaten to alter the dynamics of riverine thermal regimes. New data and tools can identify particular facets of the thermal landscape that describe ecological and management concerns and that are linked to human actions. The emerging complexity of thermal landscapes demands innovations in communication, opens the door to exciting research opportunities on the human impacts to and biological consequences of thermal variability, suggests improvements in monitoring programs to better capture empirical patterns, provides a framework for suites of actions to restore and protect the natural processes that drive thermal complexity, and indicates opportunities for better managing thermal landscapes.
Prediction of Thermal Environment in a Large Space Using Artificial Neural Network
Directory of Open Access Journals (Sweden)
Hyun-Jung Yoon
2018-02-01
Full Text Available Since the thermal environment of large space buildings such as stadiums can vary depending on the location of the stands, it is important to divide them into different zones and evaluate their thermal environment separately. The thermal environment can be evaluated using physical values measured with the sensors, but the occupant density of the stadium stands is high, which limits the locations available to install the sensors. As a method to resolve the limitations of installing the sensors, we propose a method to predict the thermal environment of each zone in a large space. We set six key thermal factors affecting the thermal environment in a large space to be predicted factors (indoor air temperature, mean radiant temperature, and clothing and the fixed factors (air velocity, metabolic rate, and relative humidity. Using artificial neural network (ANN models and the outdoor air temperature and the surface temperature of the interior walls around the stands as input data, we developed a method to predict the three thermal factors. Learning and verification datasets were established using STAR CCM+ (2016.10, Siemens PLM software, Plano, TX, USA. An analysis of each model’s prediction results showed that the prediction accuracy increased with the number of learning data points. The thermal environment evaluation process developed in this study can be used to control heating, ventilation, and air conditioning (HVAC facilities in each zone in a large space building with sufficient learning by ANN models at the building testing or the evaluation stage.
Self-constructed tree-shape high thermal conductivity nanosilver networks in epoxy.
Pashayi, Kamyar; Fard, Hafez Raeisi; Lai, Fengyuan; Iruvanti, Sushumna; Plawsky, Joel; Borca-Tasciuc, Theodorian
2014-04-21
We report the formation of high aspect ratio nanoscale tree-shape silver networks in epoxy, at low temperatures (thermal conductivity (κ) of the nanocomposite compared to the polymer matrix. The networks form through a three-step process comprising of self-assembly by diffusion limited aggregation of polyvinylpyrrolidone (PVP) coated nanoparticles, removal of PVP coating from the surface, and sintering of silver nanoparticles in high aspect ratio networked structures. Controlling self-assembly and sintering by carefully designed multistep temperature and time processing leads to κ of our silver nanocomposites that are up to 300% of the present state of the art polymer nanocomposites at similar volume fractions. Our investigation of the κ enhancements enabled by tree-shaped network nanocomposites provides a basis for the development of new polymer nanocomposites for thermal transport and storage applications.
A study on the evolution of crack networks under thermal fatigue loading
International Nuclear Information System (INIS)
Kamaya, Masayuki; Taheri, Said
2008-01-01
The crack network is a typical cracking morphology caused by thermal fatigue loading. It was pointed out that the crack network appeared under relatively small temperature fluctuations and did not grow deeply. In this study, the mechanism of evolution of crack network and its influence on crack growth was examined by numerical calculation. First, the stress field near two interacting cracks was investigated. It was shown that there are stress-concentration and stress-shielding zones around interacting cracks, and that cracks can form a network under the bi-axial stress condition. Secondly, a Monte Carlo simulation was developed in order to simulate the initiation and growth of cracks under thermal fatigue loading and the evolution of the crack network. The local stress field formed by pre-existing cracks was evaluated by the body force method and its role in the initiation and growth of cracks was considered. The simulation could simulate the evolution of the crack network and change in number of cracks observed in the experiments. It was revealed that reduction in the stress intensity factor due to stress feature in the depth direction under high cycle thermal fatigue loading plays an important role in the evolution of the crack network and that mechanical interaction between cracks in the network affects initiation rather than growth of cracks. The crack network appears only when the crack growth in the depth direction is interrupted. It was concluded that the emergence of the crack network is preferable for the structural integrity of cracked components
Smart thermal networks for smart cities - Introduction of concepts and measures
Schmidt, R. R.; Pol, O.; Basciotti, D.; Page, J.
2012-10-01
In order to contribute to high living standards, climate mitigation and energy supply security, future urban energy systems require a holistic approach. In particular an intelligent integration of thermal networks is necessary. This paper will briefly present the "smart city" concept and introduce an associated definition for smart thermal networks defined on three levels: 1. the interaction with urban planning processes and the interface to the overall urban energy system, 2. the adaptation of the temperature level and 3. supply and demand-side management strategies.
Directory of Open Access Journals (Sweden)
Yaolin Lin
2018-06-01
Full Text Available Thermal load and indoor comfort level are two important building performance indicators, rapid predictions of which can help significantly reduce the computation time during design optimization. In this paper, a three-step approach is used to develop and evaluate prediction models. Firstly, the Latin Hypercube Sampling Method (LHSM is used to generate a representative 19-dimensional design database and DesignBuilder is then used to obtain the thermal load and discomfort degree hours through simulation. Secondly, samples from the database are used to develop and validate seven prediction models, using data mining approaches including multilinear regression (MLR, chi-square automatic interaction detector (CHAID, exhaustive CHAID (ECHAID, back-propagation neural network (BPNN, radial basis function network (RBFN, classification and regression trees (CART, and support vector machines (SVM. It is found that the MLR and BPNN models outperform the others in the prediction of thermal load with average absolute error of less than 1.19%, and the BPNN model is the best at predicting discomfort degree hour with 0.62% average absolute error. Finally, two hybrid models—MLR (MLR + BPNN and MLR-BPNN—are developed. The MLR-BPNN models are found to be the best prediction models, with average absolute error of 0.82% in thermal load and 0.59% in discomfort degree hour.
Ghaderi, Forouzan; Ghaderi, Amir H; Ghaderi, Noushin; Najafi, Bijan
2017-01-01
Background: The thermal conductivity of fluids can be calculated by several computational methods. However, these methods are reliable only at the confined levels of density, and there is no specific computational method for calculating thermal conductivity in the wide ranges of density. Methods: In this paper, two methods, an Artificial Neural Network (ANN) approach and a computational method established upon the Rainwater-Friend theory, were used to predict the value of thermal conductivity in all ranges of density. The thermal conductivity of six refrigerants, R12, R14, R32, R115, R143, and R152 was predicted by these methods and the effectiveness of models was specified and compared. Results: The results show that the computational method is a usable method for predicting thermal conductivity at low levels of density. However, the efficiency of this model is considerably reduced in the mid-range of density. It means that this model cannot be used at density levels which are higher than 6. On the other hand, the ANN approach is a reliable method for thermal conductivity prediction in all ranges of density. The best accuracy of ANN is achieved when the number of units is increased in the hidden layer. Conclusion: The results of the computational method indicate that the regular dependence between thermal conductivity and density at higher densities is eliminated. It can develop a nonlinear problem. Therefore, analytical approaches are not able to predict thermal conductivity in wide ranges of density. Instead, a nonlinear approach such as, ANN is a valuable method for this purpose.
Electrical Thermal Network for Direct Contact Membrane Distillation Modeling and Analysis
Karam, Ayman M.
2015-02-04
Membrane distillation is an emerging water distillation technology that offers several advantages compared to conventional water desalination processes. Although progress has been made to model and understand the physics of the process, many studies are based on steady-state assumptions or are computationally not appropriate for real time control. This paper presents the derivation of a novel dynamical model, based on analogy between electrical and thermal systems, for direct contact membrane distillation (DCMD). The proposed model captures the dynamics of temperature distribution and distilled water flux. To demonstrate the adequacy of the proposed model, validation with transient and steady-state experimental data is presented.
A Fast Electro-Thermal Co-Simulation Modeling Approach for SiC Power MOSFETs
DEFF Research Database (Denmark)
Ceccarelli, Lorenzo; Bahman, Amir Sajjad; Iannuzzo, Francesco
2017-01-01
The purpose of this work is to propose a novel electro-thermal co-simulation approach for the new generation of SiC MOSFETs, by development of a PSpice-based compact and physical SiC MOSFET model including temperature dependency of several parameters and a Simulink-based thermal network. The PSpice...... the FEM simulation of the DUT’s structure, performed in ANSYS Icepack. A MATLAB script is used to process the simulation data and feed the needed settings and parameters back into the simulation. The parameters for a CREE 1.2 kV/30 A SiC MOSFET have been identified and the electro-thermal model has been...
Lumped-Element Dynamic Electro-Thermal model of a superconducting magnet
Ravaioli, E.; Auchmann, B.; Maciejewski, M.; ten Kate, H. H. J.; Verweij, A. P.
2016-12-01
Modeling accurately electro-thermal transients occurring in a superconducting magnet is challenging. The behavior of the magnet is the result of complex phenomena occurring in distinct physical domains (electrical, magnetic and thermal) at very different spatial and time scales. Combined multi-domain effects significantly affect the dynamic behavior of the system and are to be taken into account in a coherent and consistent model. A new methodology for developing a Lumped-Element Dynamic Electro-Thermal (LEDET) model of a superconducting magnet is presented. This model includes non-linear dynamic effects such as the dependence of the magnet's differential self-inductance on the presence of inter-filament and inter-strand coupling currents in the conductor. These effects are usually not taken into account because superconducting magnets are primarily operated in stationary conditions. However, they often have significant impact on magnet performance, particularly when the magnet is subject to high ramp rates. Following the LEDET method, the complex interdependence between the electro-magnetic and thermal domains can be modeled with three sub-networks of lumped-elements, reproducing the electrical transient in the main magnet circuit, the thermal transient in the coil cross-section, and the electro-magnetic transient of the inter-filament and inter-strand coupling currents in the superconductor. The same simulation environment can simultaneously model macroscopic electrical transients and phenomena at the level of superconducting strands. The model developed is a very useful tool for reproducing and predicting the performance of conventional quench protection systems based on energy extraction and quench heaters, and of the innovative CLIQ protection system as well.
Thermal modelling using discrete vasculature for thermal therapy: a review
Kok, H.P.; Gellermann, J.; van den Berg, C.A.T.; Stauffer, P.R.; Hand, J.W.; Crezee, J.
2013-01-01
Reliable temperature information during clinical hyperthermia and thermal ablation is essential for adequate treatment control, but conventional temperature measurements do not provide 3D temperature information. Treatment planning is a very useful tool to improve treatment quality and substantial progress has been made over the last decade. Thermal modelling is a very important and challenging aspect of hyperthermia treatment planning. Various thermal models have been developed for this purpose, with varying complexity. Since blood perfusion is such an important factor in thermal redistribution of energy in in vivo tissue, thermal simulations are most accurately performed by modelling discrete vasculature. This review describes the progress in thermal modelling with discrete vasculature for the purpose of hyperthermia treatment planning and thermal ablation. There has been significant progress in thermal modelling with discrete vasculature. Recent developments have made real-time simulations possible, which can provide feedback during treatment for improved therapy. Future clinical application of thermal modelling with discrete vasculature in hyperthermia treatment planning is expected to further improve treatment quality. PMID:23738700
Directory of Open Access Journals (Sweden)
Kyung-Il Chin
2013-08-01
Full Text Available This study proposes an artificial neural network (ANN-based thermal control method for buildings with double skin envelopes that has rational relationships between the ANN model input and output. The relationship between the indoor air temperature and surrounding environmental factors was investigated based on field measurement data from an actual building. The results imply that the indoor temperature was not significantly influenced by vertical solar irradiance, but by the outdoor and cavity temperature. Accordingly, a new ANN model developed in this study excluded solar irradiance as an input variable for predicting the future indoor temperature. The structure and learning method of this new ANN model was optimized, followed by the performance tests of a variety of internal and external envelope opening strategies for the heating and cooling seasons. The performance tests revealed that the optimized ANN-based logic yielded better temperature conditions than the non-ANN based logic. This ANN-based logic increased overall comfortable periods and decreased the frequency of overshoots and undershoots out of the thermal comfort range. The ANN model proved that it has the potential to be successfully applied in the temperature control logic for double skin-enveloped buildings. The ANN model, which was proposed in this study, effectively predicted future indoor temperatures for the diverse opening strategies. The ANN-based logic optimally determined the operation of heating and cooling systems as well as opening conditions for the double skin envelopes.
International Nuclear Information System (INIS)
Chen, Mingbiao; Bai, Fanfei; Song, Wenji; Lv, Jie; Lin, Shili
2017-01-01
Highlights: • 2D network equivalent circuit considers the interplay of cell units. • The temperature non-uniformity Φ of multilayer model is bigger than that of lumped model. • The temperature non-uniformity is quantified and the reason of non-uniformity is analyzed. • Increasing the thermal conductivity of the separator can effectively relieve the heat spot effect of ISC. - Abstract: As the electrical and thermal characteristic will affect the batteries’ safety, performance, calendar life and capacity fading, an electro-thermal coupled model for pouch battery LiFePO_4/C is developed in normal discharge and internal short circuit process. The battery is discretized into many cell elements which are united as a 2D network equivalent circuit. The electro-thermal model is solved with finite difference method. Non-uniformity of current distribution and temperature distribution is simulated and the result is validated with experiment data at various discharge rates. Comparison of the lumped model and the multilayer structure model shows that the temperature non-uniformity Φ of multilayer model is bigger than that of lumped model and shows more precise. The temperature non-uniformity is quantified and the reason of non-uniformity is analyzed. The electro-thermal model can also be used to guide the safety design of battery. The temperature of the ISC element near tabs is the highest because the equivalent resistance of the external circuit (not including the ISC element) is the smallest when the resistance of cell units is small. It is found that increasing the thermal conductivity of integrated layer can effectively relieve the heat spot effect of ISC.
The analysis of thermal network of district heating system from investor point of view
Takács, Ján; Rácz, Lukáš
2016-06-01
The hydraulics of a thermal network of a district heating system is a very important issue, to which not enough attention is often paid. In this paper the authors want to point out some of the important aspects of the design and operation of thermal networks in district heating systems. The design boundary conditions of a heat distribution network and the requirements on active pressure - circulation pump - influencing the operation costs of the centralized district heating system as a whole, are analyzed in detail. The heat generators and the heat exchange stations are designed according to the design heat loads after thermal insulation, and modern boiler units are installed in the heating plant.
Thermal Error Test and Intelligent Modeling Research on the Spindle of High Speed CNC Machine Tools
Luo, Zhonghui; Peng, Bin; Xiao, Qijun; Bai, Lu
2018-03-01
Thermal error is the main factor affecting the accuracy of precision machining. Through experiments, this paper studies the thermal error test and intelligent modeling for the spindle of vertical high speed CNC machine tools in respect of current research focuses on thermal error of machine tool. Several testing devices for thermal error are designed, of which 7 temperature sensors are used to measure the temperature of machine tool spindle system and 2 displacement sensors are used to detect the thermal error displacement. A thermal error compensation model, which has a good ability in inversion prediction, is established by applying the principal component analysis technology, optimizing the temperature measuring points, extracting the characteristic values closely associated with the thermal error displacement, and using the artificial neural network technology.
Thermal management of a PEMFC stack by 3D nodal modeling
Energy Technology Data Exchange (ETDEWEB)
Dumercy, L.; Glises, R.; Kauffmann, J.M. [Laboratoire de Recherche en Electronique, Electrotechnique et Systemes (L2ES), UFC-UTBM EA 3898, Rue T. MIEG, 90010 Belfort cedex (France); Louahlia-Gualous, H. [FEMTO-ST, CNRS UMR6174, CREST, 2 av. Jean Moulin, 90000 Belfort (France)
2006-05-19
This paper describes a 3D thermal modeling by a nodes network model for two PEMFC of 150 and 500W (respectively, 3 and 20 cells). Modeling are realized for each case for one cell before to be integrated on all the stack. Absolute temperatures of H{sub 2}, air and water channels are used as Dirichlet conditions. Temperatures of external surfaces are obtained thanks to an infrared thermographic camera. Final external heat fluxes are deduced from the integrated model. (author)
Characterization of an Isolated Kidney's Vasculature for Use in Bio-Thermal Modeling
Payne, Allison H.; Parker, Dennis L.; Moellmer, Jeff; Roemer, Robert B.; Clifford, Sarah
2007-05-01
Accurate bio-thermal modeling requires site-specific modeling of discrete vascular anatomy. Presented herewith are several steps that have been developed to describe the vessel network of isolated canine and bovine kidneys. These perfused, isolated kidneys provide an environment to repeatedly test and improve acquisition methods to visualize the vascular anatomy, as well as providing a method to experimentally validate discrete vasculature thermal models. The organs are preserved using a previously developed methodology that keeps the vasculature intact, allowing for the organ to be perfused. It also allows for the repeated fixation and re-hydration of the same organ, permitting the comparison of various methods and models. The organ extraction, alcohol preservation, and perfusion of the organ are described. The vessel locations were obtained through a high-resolution time-of-flight (TOF) magnetic resonance angiography (MRA) technique. Sequential improvements of both the experimental setup used for this acquisition, as well as MR sequence development are presented. The improvements in MR acquisition and experimental setup improved the number of vessels seen in both the raw data and segmented images by 50%. An automatic vessel centerline extraction algorithm describes both vessel location and genealogy. Centerline descriptions also allows for vessel diameter and flow rate determination, providing valuable input parameters for the discrete vascular thermal model. Characterized vessels networks of both canine and bovine kidneys are presented. While these tools have been developed in an ex vivo environment, all steps can be applied to in vivo applications.
MATHEMATICAL MODELLING OF OPERATION HEAT NETWORKS IN VIEW OF HEAT LOSS
Directory of Open Access Journals (Sweden)
ZBARAZ L. I.
2016-08-01
Full Text Available Goal. In recent years, due to a significant rise in price of energy, the reduction of direct costs for heating becomes a priority. In the utilities especially important to optimization of energy heating system equipment. During transport of thermal energy in the distribution networks thermal losses occur along the length of the hydraulic pipes and the coolant pumping losses. These loss-dependence of the particular distribution network. Changing temperature and the hydraulic regime at the source necessary to achieve the minimum cost of transport for today acting tariffs for energy. Scientific novelty. The studies received law changes head to the source at the qualitative and quantitative methods of regulation. Results. A mathematical model of an extensive network of decentralized heat source heating, which are analyzed using different methods of regulating and found the best.
Modeling the citation network by network cosmology.
Xie, Zheng; Ouyang, Zhenzheng; Zhang, Pengyuan; Yi, Dongyun; Kong, Dexing
2015-01-01
Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well.
Smart thermal networks for smart cities – Introduction of concepts and measures
Directory of Open Access Journals (Sweden)
Basciotti D.
2012-10-01
Full Text Available In order to contribute to high living standards, climate mitigation and energy supply security, future urban energy systems require a holistic approach. In particular an intelligent integration of thermal networks is necessary. This paper will briefly present the “smart city” concept and introduce an associated definition for smart thermal networks defined on three levels: 1. the interaction with urban planning processes and the interface to the overall urban energy system, 2. the adaptation of the temperature level and 3. supply and demand-side management strategies.
Integration of Decentralized Thermal Storages Within District Heating (DH Networks
Directory of Open Access Journals (Sweden)
Schuchardt Georg K.
2016-12-01
Full Text Available Thermal Storages and Thermal Accumulators are an important component within District Heating (DH systems, adding flexibility and offering additional business opportunities for these systems. Furthermore, these components have a major impact on the energy and exergy efficiency as well as the heat losses of the heat distribution system. Especially the integration of Thermal Storages within ill-conditioned parts of the overall DH system enhances the efficiency of the heat distribution. Regarding an illustrative and simplified example for a DH system, the interactions of different heat storage concepts (centralized and decentralized and the heat losses, energy and exergy efficiencies will be examined by considering the thermal state of the heat distribution network.
Artificial Neural Network based control for PV/T panel to track optimum thermal and electrical power
International Nuclear Information System (INIS)
Ben Ammar, Majed; Chaabene, Maher; Chtourou, Zied
2013-01-01
Highlights: ► We establish a state model of PV/T panel. ► We study the effect of mass flow rate on PV/T efficiency. ► A real time PV/T control algorithm is proposed. ► A model based optimal thermal and electrical power operation point is tracked. - Abstract: As solar energy is intermittent, many algorithms and electronics have been developed to track the maximum power generation from photovoltaic and thermal panels. Following technological advances, these panels are gathered into one unit: PV/T system. PV/T delivers simultaneously two kinds of power: electrical power and thermal power. Nevertheless, no control systems have been developed in order to track maximum power generation from PV/T system. This paper suggests a PV/T control algorithm based on Artificial Neural Network (ANN) to detect the optimal power operating point (OPOP) by considering PV/T model behavior. The OPOP computes the optimum mass flow rate of PV/T for a considered irradiation and ambient temperature. Simulation results demonstrate great concordance between OPOP model based calculation and ANN outputs.
International Nuclear Information System (INIS)
Max, G
2011-01-01
Traffic models in computer networks can be described as a complicated system. These systems show non-linear features and to simulate behaviours of these systems are also difficult. Before implementing network equipments users wants to know capability of their computer network. They do not want the servers to be overloaded during temporary traffic peaks when more requests arrive than the server is designed for. As a starting point for our study a non-linear system model of network traffic is established to exam behaviour of the network planned. The paper presents setting up a non-linear simulation model that helps us to observe dataflow problems of the networks. This simple model captures the relationship between the competing traffic and the input and output dataflow. In this paper, we also focus on measuring the bottleneck of the network, which was defined as the difference between the link capacity and the competing traffic volume on the link that limits end-to-end throughput. We validate the model using measurements on a working network. The results show that the initial model estimates well main behaviours and critical parameters of the network. Based on this study, we propose to develop a new algorithm, which experimentally determines and predict the available parameters of the network modelled.
Thermal and Fluid Modeling of the CRYogenic Orbital TEstbed (CRYOTE) Ground Test Article (GTA)
Piryk, David; Schallhorn, Paul; Walls, Laurie; Stopnitzky, Benny; Rhys, Noah; Wollen, Mark
2012-01-01
The purpose of this study was to anchor thermal and fluid system models to data acquired from a ground test article (GTA) for the CRYogenic Orbital TEstbed - CRYOTE. To accomplish this analysis, it was broken into four primary tasks. These included model development, pre-test predictions, testing support at Marshall Space Flight Center (MSFC} and post-test correlations. Information from MSFC facilitated the task of refining and correlating the initial models. The primary goal of the modeling/testing/correlating efforts was to characterize heat loads throughout the ground test article. Significant factors impacting the heat loads included radiative environments, multi-layer insulation (MLI) performance, tank fill levels, tank pressures, and even contact conductance coefficients. This paper demonstrates how analytical thermal/fluid networks were established, and it includes supporting rationale for specific thermal responses seen during testing.
Doe, T.; McLaren, R.; Finilla, A.
2017-12-01
An enduring legacy of Paul Witherspoon and his students and colleagues has been both the development of geothermal energy and the bases of modern fractured-rock hydrogeology. One of the seminal contributions to the geothermal field was Gringarten, Witherspoon, and Ohnishi's analytical models for enhanced geothermal systems. Although discrete fracture network (DFN) modeling developed somewhat independently in the late 1970s, Paul Witherspoon's foresight in promoting underground in situ testing at the Stripa Mine in Sweden was a major driver in Lawrence Berkeley Laboratory's contributions to its development.This presentation looks extensions of Gringarten's analytical model into discrete fracture network modeling as a basis for providing further insights into the challenges and opportunities of engineered geothermal systems. The analytical solution itself has many insightful applications beyond those presented in the original paper. The definition of dimensionless time by itself shows that thermal breakthrough has a second power dependence on surface area and on flow rate. The fracture intensity also plays a strong role, as it both increases the surface area and decrease his flow rate per fracture. The improvement of EGS performance with fracture intensity reaches a limit where thermal depletion of the rock lags only slightly behind the thermal breakthrough of cold water in the fracture network.Simple network models, which couple a DFN generator (FracMan) with a hydrothermally coupled flow solver (HydroGeoSphere) expand on Gringarten's concepts to show that realistic heterogeneity of spacing and transmissivity significantly degrades EGS performance. EGS production in networks of stimulated fractures initially follows Gringarten's type curves, with a later deviation is the smaller rock blocks thermally deplete and the entire stimulated volume acts as a single sink. Three-dimensional models of EGS performance show the critical importance of the relative magnitudes of
Human Thermal Model Evaluation Using the JSC Human Thermal Database
Bue, Grant; Makinen, Janice; Cognata, Thomas
2012-01-01
Human thermal modeling has considerable long term utility to human space flight. Such models provide a tool to predict crew survivability in support of vehicle design and to evaluate crew response in untested space environments. It is to the benefit of any such model not only to collect relevant experimental data to correlate it against, but also to maintain an experimental standard or benchmark for future development in a readily and rapidly searchable and software accessible format. The Human thermal database project is intended to do just so; to collect relevant data from literature and experimentation and to store the data in a database structure for immediate and future use as a benchmark to judge human thermal models against, in identifying model strengths and weakness, to support model development and improve correlation, and to statistically quantify a model s predictive quality. The human thermal database developed at the Johnson Space Center (JSC) is intended to evaluate a set of widely used human thermal models. This set includes the Wissler human thermal model, a model that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. These models are statistically compared to the current database, which contains experiments of human subjects primarily in air from a literature survey ranging between 1953 and 2004 and from a suited experiment recently performed by the authors, for a quantitative study of relative strength and predictive quality of the models.
Directory of Open Access Journals (Sweden)
Dewei Tang
2017-03-01
Full Text Available The main task of the third Chinese lunar exploration project is to obtain soil samples that are greater than two meters in length and to acquire bedding information from the surface of the moon. The driving component is the power output unit of the drilling system in the lander; it provides drilling power for core drilling tools. High temperatures can cause the sensors, permanent magnet, gears, and bearings to suffer irreversible damage. In this paper, a thermal analysis model for this driving component, based on the thermal network method (TNM was established and the model was solved using the quasi-Newton method. A vacuum test platform was built and an experimental verification method (EVM was applied to measure the surface temperature of the driving component. Then, the TNM was optimized, based on the principle of heat distribution. Through comparative analyses, the reasonableness of the TNM is validated. Finally, the static temperature field of the driving component was predicted and the “safe working times” of every mode are given.
Thermal fatigue. Materials modelling
International Nuclear Information System (INIS)
Siegele, D.; Fingerhuth, J.; Mrovec, M.
2012-01-01
In the framework of the ongoing joint research project 'Thermal Fatigue - Basics of the system-, outflow- and material-characteristics of piping under thermal fatigue' funded by the German Federal Ministry of Education and Research (BMBF) fundamental numerical and experimental investigations on the material behavior under transient thermal-mechanical stress conditions (high cycle fatigue V HCF and low cycle fatigue - LCF) are carried out. The primary objective of the research is the further development of simulation methods applied in safety evaluations of nuclear power plant components. In this context the modeling of crack initiation and growth inside the material structure induced by varying thermal loads are of particular interest. Therefore, three scientific working groups organized in three sub-projects of the joint research project are dealing with numerical modeling and simulation at different levels ranging from atomistic to micromechanics and continuum mechanics, and in addition corresponding experimental data for the validation of the numerical results and identification of the parameters of the associated material models are provided. The present contribution is focused on the development and experimental validation of material models and methods to characterize the damage evolution and the life cycle assessment as a result of thermal cyclic loading. The individual purposes of the subprojects are as following: - Material characterization, Influence of temperature and surface roughness on fatigue endurances, biaxial thermo-mechanical behavior, experiments on structural behavior of cruciform specimens and scatter band analysis (IfW Darmstadt) - Life cycle assessment with micromechanical material models (MPA Stuttgart) - Life cycle assessment with atomistic and damage-mechanical material models associated with material tests under thermal fatigue (Fraunhofer IWM, Freiburg) - Simulation of fatigue crack growth, opening and closure of a short crack under
Amiribavandpour, Parisa; Shen, Weixiang; Mu, Daobin; Kapoor, Ajay
2015-06-01
A theoretical electrochemical thermal model combined with a thermal resistive network is proposed to investigate thermal behaviours of a battery pack. The combined model is used to study heat generation and heat dissipation as well as their influences on the temperatures of the battery pack with and without a fan under constant current discharge and variable current discharge based on electric vehicle (EV) driving cycles. The comparison results indicate that the proposed model improves the accuracy in the temperature predication of the battery pack by 2.6 times. Furthermore, a large battery pack with four of the investigated battery packs in series is simulated in the presence of different ambient temperatures. The simulation results show that the temperature of the large battery pack at the end of EV driving cycles can reach to 50 °C or 60 °C in high ambient temperatures. Therefore, thermal management system in EVs is required to maintain the battery pack within the safe temperature range.
Dynamic indoor thermal comfort model identification based on neural computing PMV index
International Nuclear Information System (INIS)
Sahari, K S Mohamed; Jalal, M F Abdul; Homod, R Z; Eng, Y K
2013-01-01
This paper focuses on modelling and simulation of building dynamic thermal comfort control for non-linear HVAC system. Thermal comfort in general refers to temperature and also humidity. However in reality, temperature or humidity is just one of the factors affecting the thermal comfort but not the main measures. Besides, as HVAC control system has the characteristic of time delay, large inertia, and highly nonlinear behaviour, it is difficult to determine the thermal comfort sensation accurately if we use traditional Fanger's PMV index. Hence, Artificial Neural Network (ANN) has been introduced due to its ability to approximate any nonlinear mapping. Using ANN to train, we can get the input-output mapping of HVAC control system or in other word; we can propose a practical approach to identify thermal comfort of a building. Simulations were carried out to validate and verify the proposed method. Results show that the proposed ANN method can track down the desired thermal sensation for a specified condition space.
Thermal sensation models: a systematic comparison.
Koelblen, B; Psikuta, A; Bogdan, A; Annaheim, S; Rossi, R M
2017-05-01
Thermal sensation models, capable of predicting human's perception of thermal surroundings, are commonly used to assess given indoor conditions. These models differ in many aspects, such as the number and type of input conditions, the range of conditions in which the models can be applied, and the complexity of equations. Moreover, the models are associated with various thermal sensation scales. In this study, a systematic comparison of seven existing thermal sensation models has been performed with regard to exposures including various air temperatures, clothing thermal insulation, and metabolic rate values after a careful investigation of the models' range of applicability. Thermo-physiological data needed as input for some of the models were obtained from a mathematical model for human physiological responses. The comparison showed differences between models' predictions for the analyzed conditions, mostly higher than typical intersubject differences in votes. Therefore, it can be concluded that the choice of model strongly influences the assessment of indoor spaces. The issue of comparing different thermal sensation scales has also been discussed. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
DEFF Research Database (Denmark)
Bahman, Amir Sajjad; Ma, Ke; Blaabjerg, Frede
2018-01-01
Detailed thermal dynamics of high power IGBT modules are important information for the reliability analysis and thermal design of power electronic systems. However, the existing thermal models have their limits to correctly predict these complicated thermal behavior in the IGBTs: The typically used...... thermal model based on one-dimensional RC lumps have limits to provide temperature distributions inside the device, moreover some variable factors in the real-field applications like the cooling and heating conditions of the converter cannot be adapted. On the other hand, the more advanced three......-dimensional thermal models based on Finite Element Method (FEM) need massive computations, which make the long-term thermal dynamics difficult to calculate. In this paper, a new lumped three-dimensional thermal model is proposed, which can be easily characterized from FEM simulations and can acquire the critical...
DEFF Research Database (Denmark)
Andersen, Kasper Winther
Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...
Modelling reverse characteristics of power LEDs with thermal phenomena taken into account
International Nuclear Information System (INIS)
Ptak, Przemysław; Górecki, Krzysztof
2016-01-01
This paper refers to modelling characteristics of power LEDs with a particular reference to thermal phenomena. Special attention is paid to modelling characteristics of the circuit protecting the considered device against the excessive value of the reverse voltage and to the description of the temperature influence on optical power. The network form of the worked out model is presented and some results of experimental verification of this model for the selected diodes operating at different cooling conditions are described. The very good agreement between the calculated and measured characteristics is obtained
Vafaei, Masoud; Afrand, Masoud; Sina, Nima; Kalbasi, Rasool; Sourani, Forough; Teimouri, Hamid
2017-01-01
In this paper, the thermal conductivity ratio of MgO-MWCNTs/EG hybrid nanofluids has been predicted by an optimal artificial neural network at solid volume fractions of 0.05%, 0.1%, 0.15%, 0.2%, 0.4% and 0.6% in the temperature range of 25-50 °C. In this way, at the first, thirty six experimental data was presented to determine the thermal conductivity ratio of the hybrid nanofluid. Then, four optimal artificial neural networks with 6, 8, 10 and 12 neurons in hidden layer were designed to predict the thermal conductivity ratio of the nanofluid. The comparison between four optimal ANN results and experimental showed that the ANN with 12 neurons in hidden layer was the best model. Moreover, the results obtained from the best ANN indicated the maximum deviation margin of 0.8%.
Thermal performance prediction of UO2 pellet partly containing 9%w tungsten network
International Nuclear Information System (INIS)
Suwardi
2008-01-01
Sintered UO 2 exhibits very stable in reactor core compared to UC, UN, U metal and its alloys. However, its thermal conductivity is very low (2.about.5 W/m K), that limits its performance. UO 2 pellet containing Tungsten network invented by Song improves considerably its conductivity. The paper reports an analysis of thermal performance for UO 2 pellet that contains partly or wholly with 9% b. of Tungsten. The tungsten network having a high melting point and excellent thermal conductivity is continuously formed around UO 2 grains. Since the presence of network decreases the amount of fissile material and the burn up of fissile material is higher in the near surface zone of pellet but high temperature zone that releases low conductivity fission gas to the gap located in inner part of pellet, the analysis has been done for different outer radial-portion of tungsten-free pellet. The analysis takes into account the correction factor for pellet conductivity related to both pore and temperature distribution and high burn up effect. The gap conductance has been considered invariable since decrease caused by wider gap size related to lower pellet expansion is compensated by increase caused by fewer of refractory fission gas released. The results (47 kw/m, 40% burnup) show temperature decrease in all of pellet position containing W network. Pellet containing 9%b. tungsten network lower consecutively its center line temperature from 1578 to 1406, 1292, 1231, 1192, 1111, and 1038 deg C for 0, 50, 67, 75, 80, 90, and 100 % portion of network. An 80 to 90 % portion of inner pellet containing tungsten network can be considered a best fuel design. This preliminary analysis is prospective and more realistic one is recommended. (author)
RADYN Simulations of Non-thermal and Thermal Models of Ellerman Bombs
Energy Technology Data Exchange (ETDEWEB)
Hong, Jie; Ding, M. D. [School of Astronomy and Space Science, Nanjing University, Nanjing 210023 (China); Carlsson, Mats, E-mail: dmd@nju.edu.cn [Institute of Theoretical Astrophysics, University of Oslo, P.O. Box 1029 Blindern, NO-0315 Oslo (Norway)
2017-08-20
Ellerman bombs (EBs) are brightenings in the H α line wings that are believed to be caused by magnetic reconnection in the lower atmosphere. To study the response and evolution of the chromospheric line profiles, we perform radiative hydrodynamic simulations of EBs using both non-thermal and thermal models. Overall, these models can generate line profiles that are similar to observations. However, in non-thermal models we find dimming in the H α line wings and continuum when the heating begins, while for the thermal models dimming occurs only in the H α line core, and with a longer lifetime. This difference in line profiles can be used to determine whether an EB is dominated by non-thermal heating or thermal heating. In our simulations, if a higher heating rate is applied, then the H α line will be unrealistically strong and there are still no clear UV burst signatures.
RADYN Simulations of Non-thermal and Thermal Models of Ellerman Bombs
Hong, Jie; Carlsson, Mats; Ding, M. D.
2017-08-01
Ellerman bombs (EBs) are brightenings in the Hα line wings that are believed to be caused by magnetic reconnection in the lower atmosphere. To study the response and evolution of the chromospheric line profiles, we perform radiative hydrodynamic simulations of EBs using both non-thermal and thermal models. Overall, these models can generate line profiles that are similar to observations. However, in non-thermal models we find dimming in the Hα line wings and continuum when the heating begins, while for the thermal models dimming occurs only in the Hα line core, and with a longer lifetime. This difference in line profiles can be used to determine whether an EB is dominated by non-thermal heating or thermal heating. In our simulations, if a higher heating rate is applied, then the Hα line will be unrealistically strong and there are still no clear UV burst signatures.
International Nuclear Information System (INIS)
Yudov, Y.V.
2001-01-01
The functional part of the KORSAR computer code is based on the computational unit for the reactor system thermal-hydraulics and other thermal power systems with water cooling. The two-phase flow dynamics of the thermal-hydraulic network is modelled by KORSAR in one-dimensional two-fluid (non-equilibrium and nonhomogeneous) approximation with the same pressure of both phases. Each phase is characterized by parameters averaged over the channel sections, and described by the conservation equations for mass, energy and momentum. The KORSAR computer code relies upon a novel approach to mathematical modelling of two-phase dispersed-annular flows. This approach allows a two-fluid model to differentiate the effects of the liquid film and droplets in the gas core on the flow characteristics. A semi-implicit numerical scheme has been chosen for deriving discrete analogs the conservation equations in KORSAR. In the semi-implicit numerical scheme, solution of finite-difference equations is reduced to the problem of determining the pressure field at a new time level. For the one-channel case, the pressure field is found from the solution of a system of linear algebraic equations by using the tri-diagonal matrix method. In the branched network calculation, the matrix of coefficients in the equations describing the pressure field is no longer tri-diagonal but has a sparseness structure. In this case, the system of linear equations for the pressure field can be solved with any of the known classical methods. Such an approach is implemented in the existing best-estimate thermal-hydraulic computer codes (TRAC, RELAP5, etc.) For the KORSAR computer code, we have developed a new non-iterative method for calculating the pressure field in the network of any topology. This method is based on the tri-diagonal matrix method and performs well when solving the thermal-hydraulic network problems. (author)
Workshop on Thermal Field Theory to Neural Networks
Veneziano, Gabriele; Aurenche, Patrick
1996-01-01
Tanguy Altherr was a Fellow in the Theory Division at CERN, on leave from LAPP (CNRS) Annecy. At the time of his accidental death in July 1994, he was only 31.A meeting was organized at CERN, covering the various aspects of his scientific interests: thermal field theory and its applications to hot or dense media, neural networks and its applications to high energy data analysis. Speakers were among his closest collaborators and friends.
Momentum integral network method for thermal-hydraulic transient analysis
International Nuclear Information System (INIS)
Van Tuyle, G.J.
1983-01-01
A new momentum integral network method has been developed, and tested in the MINET computer code. The method was developed in order to facilitate the transient analysis of complex fluid flow and heat transfer networks, such as those found in the balance of plant of power generating facilities. The method employed in the MINET code is a major extension of a momentum integral method reported by Meyer. Meyer integrated the momentum equation over several linked nodes, called a segment, and used a segment average pressure, evaluated from the pressures at both ends. Nodal mass and energy conservation determined nodal flows and enthalpies, accounting for fluid compression and thermal expansion
Energy Technology Data Exchange (ETDEWEB)
Sundberg, Jan; Wrafter, John; Laendell, Maerta (Geo Innova AB (Sweden)); Back, Paer-Erik; Rosen, Lars (Sweco AB (Sweden))
2008-11-15
This report present the results of thermal modelling work for the Forsmark area carried out during modelling stage 2.3. The work complements the main modelling efforts carried out during modelling stage 2.2. A revised spatial statistical description of the rock mass thermal conductivity for rock domain RFM045 is the main result of this work. Thermal modelling of domain RFM045 in Forsmark model stage 2.2 gave lower tail percentiles of thermal conductivity that were considered to be conservatively low due to the way amphibolite, the rock type with the lowest thermal conductivity, was modelled. New and previously available borehole data are used as the basis for revised stochastic geological simulations of domain RFM045. By defining two distinct thermal subdomains, these simulations have succeeded in capturing more of the lithological heterogeneity present. The resulting thermal model for rock domain RFM045 is, therefore, considered to be more realistic and reliable than that presented in model stage 2.2. The main conclusions of modelling efforts in model stage 2.3 are: - Thermal modelling indicates a mean thermal conductivity for domain RFM045 at the 5 m scale of 3.56 W/(mK). This is slightly higher than the value of 3.49 W/(mK) derived in model stage 2.2. - The variance decreases and the lower tail percentiles increase as the scale of observation increases from 1 to 5 m. Best estimates of the 0.1 percentile of thermal conductivity for domain RFM045 are 2.24 W/(mK) for the 1 m scale and 2.36 W/(mK) for the 5 m scale. This can be compared with corresponding values for domain RFM029 of 2.30 W/(mK) for the 1 m scale and 2.87 W/(mK)for the 5 m scale. - The reason for the pronounced lower tail in the thermal conductivity distribution for domain RFM045 is the presence of large bodies of the low-conductive amphibolite. - The modelling results for domain RFM029 presented in model stage 2.2 are still applicable. - As temperature increases, the thermal conductivity decreases
Thermal evolution of the Schwinger model with matrix product operators
International Nuclear Information System (INIS)
Banuls, M.C.; Cirac, J.I.; Cichy, K.; Jansen, K.; Saito, H.
2015-10-01
We demonstrate the suitability of tensor network techniques for describing the thermal evolution of lattice gauge theories. As a benchmark case, we have studied the temperature dependence of the chiral condensate in the Schwinger model, using matrix product operators to approximate the thermal equilibrium states for finite system sizes with non-zero lattice spacings. We show how these techniques allow for reliable extrapolations in bond dimension, step width, system size and lattice spacing, and for a systematic estimation and control of all error sources involved in the calculation. The reached values of the lattice spacing are small enough to capture the most challenging region of high temperatures and the final results are consistent with the analytical prediction by Sachs and Wipf over a broad temperature range.
Modeling of thermal coupling in VO2-based oscillatory neural networks
Velichko, Andrey; Belyaev, Maksim; Putrolaynen, Vadim; Perminov, Valentin; Pergament, Alexander
2018-01-01
In this study, we have demonstrated the possibility of using the thermal coupling to control the dynamics of operation of coupled VO2 oscillators. Based on the example of a 'switch-microheater' pair, we have explored the synchronization and dissynchronization modes of a single oscillator with respect to an external harmonic heat impact. The features of changes in the spectra are shown, in particular, the effect of the natural frequency attraction to the affecting signal frequency and the self-oscillation noise reduction effects at synchronization. The time constant of the temperature effect for the considered system configuration is in the range 7-140 μs, which allows operation in the oscillation frequency range of up to ∼70 kHz. A model estimate of the minimum temperature sensitivity of the switch is δTswitch ∼ 0.2 K, and the effective action radius RTC of the switch-to-switch thermal coupling is not less than 25 μm. Nevertheless, as the simulation shows, the frequency range can be significantly extended up to the values of 1-30 GHz if using nanometer-scale switches (heaters). article>
Collaborative networks: Reference modeling
Camarinha-Matos, L.M.; Afsarmanesh, H.
2008-01-01
Collaborative Networks: Reference Modeling works to establish a theoretical foundation for Collaborative Networks. Particular emphasis is put on modeling multiple facets of collaborative networks and establishing a comprehensive modeling framework that captures and structures diverse perspectives of
Neural computing thermal comfort index for HVAC systems
International Nuclear Information System (INIS)
Atthajariyakul, S.; Leephakpreeda, T.
2005-01-01
The primary purpose of a heating, ventilating and air conditioning (HVAC) system within a building is to make occupants comfortable. Without real time determination of human thermal comfort, it is not feasible for the HVAC system to yield controlled conditions of the air for human comfort all the time. This paper presents a practical approach to determine human thermal comfort quantitatively via neural computing. The neural network model allows real time determination of the thermal comfort index, where it is not practical to compute the conventional predicted mean vote (PMV) index itself in real time. The feed forward neural network model is proposed as an explicit function of the relation of the PMV index to accessible variables, i.e. the air temperature, wet bulb temperature, globe temperature, air velocity, clothing insulation and human activity. An experiment in an air conditioned office room was done to demonstrate the effectiveness of the proposed methodology. The results show good agreement between the thermal comfort index calculated from the neural network model in real time and those calculated from the conventional PMV model
Modeling thermal stress propagation during hydraulic stimulation of geothermal wells
Jansen, Gunnar; Miller, Stephen A.
2017-04-01
A large fraction of the world's water and energy resources are located in naturally fractured reservoirs within the earth's crust. Depending on the lithology and tectonic history of a formation, fracture networks can range from dense and homogeneous highly fractured networks to single large scale fractures dominating the flow behavior. Understanding the dynamics of such reservoirs in terms of flow and transport is crucial to successful application of engineered geothermal systems (also known as enhanced geothermal systems or EGS) for geothermal energy production in the future. Fractured reservoirs are considered to consist of two distinct separate media, namely the fracture and matrix space respectively. Fractures are generally thin, highly conductive containing only small amounts of fluid, whereas the matrix rock provides high fluid storage but typically has much smaller permeability. Simulation of flow and transport through fractured porous media is challenging due to the high permeability contrast between the fractures and the surrounding rock matrix. However, accurate and efficient simulation of flow through a fracture network is crucial in order to understand, optimize and engineer reservoirs. It has been a research topic for several decades and is still under active research. Accurate fluid flow simulations through field-scale fractured reservoirs are still limited by the power of current computer processing units (CPU). We present an efficient implementation of the embedded discrete fracture model, which is a promising new technique in modeling the behavior of enhanced geothermal systems. An efficient coupling strategy is determined for numerical performance of the model. We provide new insight into the coupled modeling of fluid flow, heat transport of engineered geothermal reservoirs with focus on the thermal stress changes during the stimulation process. We further investigate the interplay of thermal and poro-elastic stress changes in the reservoir
The ORC method. Effective modelling of thermal performance of multilayer building components
Energy Technology Data Exchange (ETDEWEB)
Akander, Jan
2000-02-01
The ORC Method (Optimised RC-networks) provides a means of modelling one- or multidimensional heat transfer in building components, in this context within building simulation environments. The methodology is shown, primarily applied to heat transfer in multilayer building components. For multilayer building components, the analytical thermal performance is known, given layer thickness and material properties. The aim of the ORC Method is to optimise the values of the thermal resistances and heat capacities of an RC-model such as to give model performance a good agreement with the analytical performance, for a wide range of frequencies. The optimisation procedure is made in the frequency domain, where the over-all deviation between model and analytical frequency response, in terms of admittance and dynamic transmittance, is minimised. It is shown that ORC's are effective in terms of accuracy and computational time in comparison to finite difference models when used in building simulations, in this case with IDA/ICE. An ORC configuration of five mass nodes has been found to model building components in Nordic countries well, within the application of thermal comfort and energy requirement simulations. Simple RC-networks, such as the surface heat capacity and the simple R-C-configuration are not appropriate for detailed building simulation. However, these can be used as basis for defining the effective heat capacity of a building component. An approximate method is suggested on how to determine the effective heat capacity without the use of complex numbers. This entity can be calculated on basis of layer thickness and material properties with the help of two time constants. The approximate method can give inaccuracies corresponding to 20%. In-situ measurements have been carried out in an experimental building with the purpose of establishing the effective heat capacity of external building components that are subjected to normal thermal conditions. The auxiliary
Haque, A.N.M.M.; Nguyen, H.P.; Vo, T.; Bliek, F.W.
2016-01-01
Rapid proliferation of the distributed energy resources (DERs) poses operational challenges for the low-voltage (LV) distribution networks in terms of thermal overloading of the network assets along with voltage limit violations at the connection points. A number of market-based and direct control
A nonlinear effective thermal conductivity model for carbon nanotube and nanofiber suspensions
Energy Technology Data Exchange (ETDEWEB)
Koo, J; Kang, Y [Department of Mechanical Engineering Kyung Hee University, 1, Seocheon-dong, Giheung-gu, Yongin-si, Gyeonggi-do 446-701 (Korea, Republic of); Kleinstreuer, C [Department of Mechanical and Aerospace Engineering, North Carolina State University, Campus Box 7910, 3211 Broughton Hall, Raleigh, NC 27695-7910 (United States)], E-mail: jmkoo@khu.ac.kr
2008-09-17
It has been experimentally demonstrated that suspensions of carbon nanotubes (CNTs) and nanofibers (CNFs) significantly increase the thermal conductivity of nanofluids; however, a physically sound theory of the underlying phenomenon is still missing. In this study, the nonlinear nature of the effective thermal conductivity enhancement with the particle concentration of CNT and CNF nanofluids is explained physically using the excluded volume concept. Specifically, the number of contacting CNTs and CNFs could be calculated by using the excluded volume concept, where the distance for heat to travel in a cylinder between the contacting cylinders in the thermal network of percolating CNTs and CNFs increased with the excluded volume. In contrast to the effective thermal conductivity model of Sastry et al (2008 Nanotechnology 19 055704) the present revised model could reproduce the nonlinear increase of the thermal conductivity with particle concentration, as well as the dependence on the diameter and aspect ratio of the CNTs and CNFs. It was found that the alignment of CNTs and CNFs due to the long range repulsion force decreases the excluded volume, leading to both the convex and concave nonlinear as well as linear increase of the thermal conductivity with particle concentration. The difference between various carrier fluids of the suspensions could be explained as the result of the change in the excluded volume in different base fluids.
Global thermal models of the lithosphere
Cammarano, F.; Guerri, M.
2017-12-01
Unraveling the thermal structure of the outermost shell of our planet is key for understanding its evolution. We obtain temperatures from interpretation of global shear-velocity (VS) models. Long-wavelength thermal structure is well determined by seismic models and only slightly affected by compositional effects and uncertainties in mineral-physics properties. Absolute temperatures and gradients with depth, however, are not well constrained. Adding constraints from petrology, heat-flow observations and thermal evolution of oceanic lithosphere help to better estimate absolute temperatures in the top part of the lithosphere. We produce global thermal models of the lithosphere at different spatial resolution, up to spherical-harmonics degree 24, and provide estimated standard deviations. We provide purely seismic thermal (TS) model and hybrid models where temperatures are corrected with steady-state conductive geotherms on continents and cooling model temperatures on oceanic regions. All relevant physical properties, with the exception of thermal conductivity, are based on a self-consistent thermodynamical modelling approach. Our global thermal models also include density and compressional-wave velocities (VP) as obtained either assuming no lateral variations in composition or a simple reference 3-D compositional structure, which takes into account a chemically depleted continental lithosphere. We found that seismically-derived temperatures in continental lithosphere fit well, overall, with continental geotherms, but a large variation in radiogenic heat is required to reconcile them with heat flow (long wavelength) observations. Oceanic shallow lithosphere below mid-oceanic ridges and young oceans is colder than expected, confirming the possible presence of a dehydration boundary around 80 km depth already suggested in previous studies. The global thermal models should serve as the basis to move at a smaller spatial scale, where additional thermo-chemical variations
Non-thermal transitions in a model inspired by moral decisions
International Nuclear Information System (INIS)
Alamino, Roberto C
2016-01-01
This work introduces a model in which agents of a network act upon one another according to three different kinds of moral decisions. These decisions are based on an increasing level of sophistication in the empathy capacity of the agent, a hierarchy which we name Piaget ’ s ladder . The decision strategy of the agents is non-rational, in the sense they are arbitrarily fixed, and the model presents quenched disorder given by the distribution of its defining parameters. An analytical solution for this model is obtained in the large system limit as well as a leading order correction for finite-size systems which shows that typical realisations of the model develop a phase structure with both continuous and discontinuous non-thermal transitions. (paper)
Energy Storage Thermal Safety | Transportation Research | NREL
reaction/thermal runaway, internal short circuit, and electrical/chemical/thermal network models are used contributions to the U.S. Department of Energy's Computer-Aided Engineering of Batteries (CAEBAT) project Li-ion battery geometries. Chemical components in Li-ion batteries become thermally unstable when
Discrete Modeling of Early-Life Thermal Fracture in Ceramic Nuclear Fuel
Energy Technology Data Exchange (ETDEWEB)
Spencer, Benjamin W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Huang, Hai [Idaho National Lab. (INL), Idaho Falls, ID (United States); Dolbow, John E. [Duke Univ., Durham, NC (United States); Hales, Jason D. [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2015-03-01
Fracturing of ceramic fuel pellets heavily influences performance of light water reactor (LWR) fuel. Early in the life of fuel, starting with the initial power ramp, large thermal gradients cause high tensile hoop and axial stresses in the outer region of the fuel pellets, resulting in the formation of radial and axial cracks. Circumferential cracks form due to thermal gradients that occur when the power is ramped down. These thermal cracks cause the fuel to expand radially, closing the pellet/cladding gap and enhancing the thermal conductance across that gap, while decreasing the effective conductivity of the fuel in directions normal to the cracking. At lower length scales, formation of microcracks is an important contributor to the decrease in bulk thermal conductivity that occurs over the life of the fuel as the burnup increases. Because of the important effects that fracture has on fuel performance, a realistic, physically based fracture modeling capability is essential to predict fuel behavior in a wide variety of normal and abnormal conditions. Modeling fracture within the context of the finite element method, which is based on continuous interpolations of solution variables, has always been challenging because fracture is an inherently discontinuous phenomenon. Work is underway at Idaho National Laboratory to apply two modeling techniques model fracture as a discrete displacement discontinuity to nuclear fuel: The extended finite element method (XFEM), and discrete element method (DEM). XFEM is based on the standard finite element method, but with enhancements to represent discontinuous behavior. DEM represents a solid as a network of particles connected by bonds, which can arbitrarily fail if a fracture criterion is reached. This paper presents initial results applying the aforementioned techniques to model fuel fracturing. This work has initially focused on early life behavior of ceramic LWR fuel. A coupled thermal-mechanical XFEM method that includes
Thermal fatigue. Fluid-structure interaction at thermal mixing events
International Nuclear Information System (INIS)
Schuler, X.; Herter, K.H.; Moogk, S.; Laurien, E.; Kloeren, D.; Kulenovic, R.; Kuschewski, M.
2012-01-01
In the framework of the network research project ''Thermal Fatigue - Basics of the system-, outflow- and material-characteristics of piping under thermal fatigue'' funded by the German Federal Ministry of Education and Research (BMBF) fundamental numerical and experimental investigations on the material behaviour under transient thermal-mechanical stress conditions (high cycle fatigue - HCF) are carried out. The project's background and its network of scientific working groups with their individual working tasks are briefly introduced. The main focus is especially on the joint research tasks within the sub-projects of MPA and IKE which are dealing with thermal mixing of flows in a T-junction configuration and the fluidstructure- interactions (FSI). Therefore, experiments were performed with the newly established FSI test facility at MPA which enables single-phase flow experiments of water in typical power plant piping diameters (DN40 and DN80) at high pressure (maximum 75 bar) and temperatures (maximum 280 C). The experimental results serve as validation data base for numerical modelling of thermal flow mixing by means of thermo-fluid dynamics simulations applying CFD techniques and carried out by IKE as well as for modelling of thermal and mechanical loads of the piping structure by structural mechanics simulations with FEM methods which are executed by MPA. The FSI test facility will be described inclusively the applied measurement techniques, e. g. in particular the novel near-wall LED-induced Fluorescence method for non-intrusive flow temperature measurements. First experimental data and numerical results from CFD and FEM simulations of the thermal mixing of flows in the T-junction are presented.
Zhao, Ningbo; Li, Zhiming
2017-05-19
To effectively predict the thermal conductivity and viscosity of alumina (Al₂O₃)-water nanofluids, an artificial neural network (ANN) approach was investigated in the present study. Firstly, using a two-step method, four Al₂O₃-water nanofluids were prepared respectively by dispersing different volume fractions (1.31%, 2.72%, 4.25%, and 5.92%) of nanoparticles with the average diameter of 30 nm. On this basis, the thermal conductivity and viscosity of the above nanofluids were analyzed experimentally under various temperatures ranging from 296 to 313 K. Then a radial basis function (RBF) neural network was constructed to predict the thermal conductivity and viscosity of Al₂O₃-water nanofluids as a function of nanoparticle volume fraction and temperature. The experimental results showed that both nanoparticle volume fraction and temperature could enhance the thermal conductivity of Al₂O₃-water nanofluids. However, the viscosity only depended strongly on Al₂O₃ nanoparticle volume fraction and was increased slightly by changing temperature. In addition, the comparative analysis revealed that the RBF neural network had an excellent ability to predict the thermal conductivity and viscosity of Al₂O₃-water nanofluids with the mean absolute percent errors of 0.5177% and 0.5618%, respectively. This demonstrated that the ANN provided an effective way to predict the thermophysical properties of nanofluids with limited experimental data.
Thermal computations for electronics conductive, radiative, and convective air cooling
Ellison, Gordon
2010-01-01
IntroductionPrimary mechanisms of heat flowConductionApplication example: Silicon chip resistance calculationConvectionApplication example: Chassis panel cooled by natural convectionRadiationApplication example: Chassis panel cooled only by radiation 7Illustrative example: Simple thermal network model for a heat sinked power transistorIllustrative example: Thermal network circuit for a printed circuit boardCompact component modelsIllustrative example: Pressure and thermal circuits for a forced air cooled enclosureIllustrative example: A single chip package on a printed circuit board-the proble
A neighbourhood evolving network model
International Nuclear Information System (INIS)
Cao, Y.J.; Wang, G.Z.; Jiang, Q.Y.; Han, Z.X.
2006-01-01
Many social, technological, biological and economical systems are best described by evolved network models. In this short Letter, we propose and study a new evolving network model. The model is based on the new concept of neighbourhood connectivity, which exists in many physical complex networks. The statistical properties and dynamics of the proposed model is analytically studied and compared with those of Barabasi-Albert scale-free model. Numerical simulations indicate that this network model yields a transition between power-law and exponential scaling, while the Barabasi-Albert scale-free model is only one of its special (limiting) cases. Particularly, this model can be used to enhance the evolving mechanism of complex networks in the real world, such as some social networks development
International Nuclear Information System (INIS)
Weissman, P.R.; Kieffer, H.H.
1987-01-01
The past year was one of tremendous activity because of the appearance of Halley's Comet. Observations of the comet were collected from a number of sources and compared with the detailed predictions of the comet thermal modeling program. Spacecraft observations of key physical parameters for cometary nucleus were incorporated into the thermal model and new cases run. These results have led to a much better understanding of physical processes on the nucleus and have pointed the way for further improvements to the modeling program. A model for the large-scale structure of cometary nuclei was proposed in which comets were envisioned as loosely bound agglomerations of smaller icy planetesimals, essentially a rubble pile of primordial dirty snowballs. In addition, a study of the physical history of comets was begun, concentrating on processes during formation and in the Oort cloud which would alter the volatile and nonvolatile materials in cometary nuclei from their pristine state before formation
Development of irradiated UO2 thermal conductivity model
International Nuclear Information System (INIS)
Lee, Chan Bock; Bang Je-Geon; Kim Dae Ho; Jung Youn Ho
2001-01-01
Thermal conductivity model of the irradiated UO 2 pellet was developed, based upon the thermal diffusivity data of the irradiated UO 2 pellet measured during thermal cycling. The model predicts the thermal conductivity by multiplying such separate correction factors as solid fission products, gaseous fission products, radiation damage and porosity. The developed model was validated by comparison with the variation of the measured thermal diffusivity data during thermal cycling and prediction of other UO 2 thermal conductivity models. Since the developed model considers the effect of gaseous fission products as a separate factor, it can predict variation of thermal conductivity in the rim region of high burnup UO 2 pellet where the fission gases in the matrix are precipitated into bubbles, indicating that decrease of thermal conductivity by bubble precipitation in rim region would be significantly compensated by the enhancing effect of fission gas depletion in the UO 2 matrix. (author)
Thermoacoustic model of a modified free piston Stirling engine with a thermal buffer tube
International Nuclear Information System (INIS)
Yang, Qin; Luo, Ercang; Dai, Wei; Yu, Guoyao
2012-01-01
This article presents a modified free-piston Stirling heat engine configuration in which a thermal buffer tube is added to sandwich between the hot and cold heat exchangers. Such a modified configuration may lead to an easier fabrication and lighter weight of a free piston. To analyze the thermodynamic performance of the modified free piston Stirling heat engine, thermoacoustic theory is used. In the thermoacoustic modelling, the regenerator, the free piston, and the thermal buffer tube are given at first. Then, based on linear thermoacoustic network theory, the thermal and thermodynamic networks are presented to characterize acoustic pressure and volume flow rate distributions at different interfaces, and the global performance such as the power output, the heat input and the thermal efficiency. A free piston Stirling heat engine with several hundreds of watts mechanical power output is selected as an example. The typical operating and structure parameters are as follows: frequency around 50 Hz, mean pressure around 3.0 MPa, and a diameter of free piston around 50 mm. From the analysis, it was found that the modified free-piston Stirling heat engine has almost the same thermodynamic performance as the original design, which indicates that the modified configuration is worthy to develop in future because of its mechanical simplicity and reliability.
Telecommunications network modelling, planning and design
Evans, Sharon
2003-01-01
Telecommunication Network Modelling, Planning and Design addresses sophisticated modelling techniques from the perspective of the communications industry and covers some of the major issues facing telecommunications network engineers and managers today. Topics covered include network planning for transmission systems, modelling of SDH transport network structures and telecommunications network design and performance modelling, as well as network costs and ROI modelling and QoS in 3G networks.
Thermal Radiation Effects on Thermal Explosion in Polydisperse Fuel Spray-Probabilistic Model
Directory of Open Access Journals (Sweden)
Ophir Navea
2011-06-01
Full Text Available We investigate the effect of thermal radiation on the dynamics of a thermal explosion of polydisperse fuel spray with a complete description of the chemistry via a single-step two-reactant model of general order. The polydisperse spray is modeled using a Probability Density Function (PDF. The thermal radiation energy exchange between the evaporation surface of the fuel droplets and the burning gas is described using the Marshak boundary conditions. An explicit expression of the critical condition for thermal explosion limit is derived analytically and represents a generalization of the critical parameter of the classical Semenov theory. Because we investigated the model in the range where the temperature is very high, the effect of the thermal radiation is significant.
International Nuclear Information System (INIS)
Maillot, V.
2004-01-01
We studied the behaviour of a 304 L type austenitic stainless steel submitted to thermal fatigue. Using the SPLASH equipment of CEA/SRMA we tested parallelepipedal specimens on two sides: the specimens are continuously heated by Joule effect, while two opposites faces are cyclically. cooled by a mixed spray of distilled water and compressed air. This device allows the reproduction and the study of crack networks similar to those observed in nuclear power plants, on the inner side of circuits fatigued by mixed pressurized water flows at different temperatures. The crack initiation and the network constitution at the surface were observed under different thermal conditions (Tmax = 320 deg C, ΔT between 125 and 200 deg C). The experiment produced a stress gradient in the specimen, and due to this gradient, the in-depth growth of the cracks finally stopped. The obtained crack networks were studied quantitatively by image analysis, and different parameters were studied: at the surface during the cycling, and post mortem by step-by-step layer removal by grinding. The maximal depth obtained experimentally, 2.5 mm, is relatively coherent with the finite element modelling of the SPLASH test, in which compressive stresses appear at a depth of 2 mm. Some of the crack networks obtained by thermal fatigue were also tested in isothermal fatigue crack growth under 4-point bending, at imposed load. The mechanisms of the crack selection, and the appearance of the dominating crack are described. Compared to the propagation of a single crack, the crack networks delay the propagation, depending on the severity of the crack competition for domination. The dominating crack can be at the network periphery, in that case it is not as shielded by its neighbours as a crack located in the center of the network. It can also be a straight crack surrounded by more sinuous neighbours. Indeed, on sinuous cracks, the loading is not the same all along the crack path, leading to some morphological
Hybrid photovoltaic–thermal solar collectors dynamic modeling
International Nuclear Information System (INIS)
Amrizal, N.; Chemisana, D.; Rosell, J.I.
2013-01-01
Highlights: ► A hybrid photovoltaic/thermal dynamic model is presented. ► The model, once calibrated, can predict the power output for any set of climate data. ► The physical electrical model includes explicitly thermal and irradiance dependences. ► The results agree with those obtained through steady-state characterization. ► The model approaches the junction cell temperature through the system energy balance. -- Abstract: A hybrid photovoltaic/thermal transient model has been developed and validated experimentally. The methodology extends the quasi-dynamic thermal model stated in the EN 12975 in order to involve the electrical performance and consider the dynamic behavior minimizing constraints when characterizing the collector. A backward moving average filtering procedure has been applied to improve the model response for variable working conditions. Concerning the electrical part, the model includes the thermal and radiation dependences in its variables. The results revealed that the characteristic parameters included in the model agree reasonably well with the experimental values obtained from the standard steady-state and IV characteristic curve measurements. After a calibration process, the model is a suitable tool to predict the thermal and electrical performance of a hybrid solar collector, for a specific weather data set.
Interfacing a General Purpose Fluid Network Flow Program with the SINDA/G Thermal Analysis Program
Schallhorn, Paul; Popok, Daniel
1999-01-01
A general purpose, one dimensional fluid flow code is currently being interfaced with the thermal analysis program Systems Improved Numerical Differencing Analyzer/Gaski (SINDA/G). The flow code, Generalized Fluid System Simulation Program (GFSSP), is capable of analyzing steady state and transient flow in a complex network. The flow code is capable of modeling several physical phenomena including compressibility effects, phase changes, body forces (such as gravity and centrifugal) and mixture thermodynamics for multiple species. The addition of GFSSP to SINDA/G provides a significant improvement in convective heat transfer modeling for SINDA/G. The interface development is conducted in multiple phases. This paper describes the first phase of the interface which allows for steady and quasi-steady (unsteady solid, steady fluid) conjugate heat transfer modeling.
Kariminia, Shahab; Motamedi, Shervin; Shamshirband, Shahaboddin; Piri, Jamshid; Mohammadi, Kasra; Hashim, Roslan; Roy, Chandrabhushan; Petković, Dalibor; Bonakdari, Hossein
2016-05-01
Visitors utilize the urban space based on their thermal perception and thermal environment. The thermal adaptation engages the user's behavioural, physiological and psychological aspects. These aspects play critical roles in user's ability to assess the thermal environments. Previous studies have rarely addressed the effects of identified factors such as gender, age and locality on outdoor thermal comfort, particularly in hot, dry climate. This study investigated the thermal comfort of visitors at two city squares in Iran based on their demographics as well as the role of thermal environment. Assessing the thermal comfort required taking physical measurement and questionnaire survey. In this study, a non-linear model known as the neural network autoregressive with exogenous input (NN-ARX) was employed. Five indices of physiological equivalent temperature (PET), predicted mean vote (PMV), standard effective temperature (SET), thermal sensation votes (TSVs) and mean radiant temperature ( T mrt) were trained and tested using the NN-ARX. Then, the results were compared to the artificial neural network (ANN) and the adaptive neuro-fuzzy inference system (ANFIS). The findings showed the superiority of the NN-ARX over the ANN and the ANFIS. For the NN-ARX model, the statistical indicators of the root mean square error (RMSE) and the mean absolute error (MAE) were 0.53 and 0.36 for the PET, 1.28 and 0.71 for the PMV, 2.59 and 1.99 for the SET, 0.29 and 0.08 for the TSV and finally 0.19 and 0.04 for the T mrt.
Thermal fatigue. Fluid-structure interaction at thermal mixing events
Energy Technology Data Exchange (ETDEWEB)
Schuler, X.; Herter, K.H.; Moogk, S. [Stuttgart Univ. (Germany). MPA; Laurien, E.; Kloeren, D.; Kulenovic, R.; Kuschewski, M. [Stuttgart Univ. (Germany). Inst. of Nuclear Technology and Energy Systems
2012-07-01
In the framework of the network research project ''Thermal Fatigue - Basics of the system-, outflow- and material-characteristics of piping under thermal fatigue'' funded by the German Federal Ministry of Education and Research (BMBF) fundamental numerical and experimental investigations on the material behaviour under transient thermal-mechanical stress conditions (high cycle fatigue - HCF) are carried out. The project's background and its network of scientific working groups with their individual working tasks are briefly introduced. The main focus is especially on the joint research tasks within the sub-projects of MPA and IKE which are dealing with thermal mixing of flows in a T-junction configuration and the fluidstructure- interactions (FSI). Therefore, experiments were performed with the newly established FSI test facility at MPA which enables single-phase flow experiments of water in typical power plant piping diameters (DN40 and DN80) at high pressure (maximum 75 bar) and temperatures (maximum 280 C). The experimental results serve as validation data base for numerical modelling of thermal flow mixing by means of thermo-fluid dynamics simulations applying CFD techniques and carried out by IKE as well as for modelling of thermal and mechanical loads of the piping structure by structural mechanics simulations with FEM methods which are executed by MPA. The FSI test facility will be described inclusively the applied measurement techniques, e. g. in particular the novel near-wall LED-induced Fluorescence method for non-intrusive flow temperature measurements. First experimental data and numerical results from CFD and FEM simulations of the thermal mixing of flows in the T-junction are presented.
Coevolutionary modeling in network formation
Al-Shyoukh, Ibrahim
2014-12-03
Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.
Coevolutionary modeling in network formation
Al-Shyoukh, Ibrahim; Chasparis, Georgios; Shamma, Jeff S.
2014-01-01
Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.
Sohrabi, Salman; Liu, Yaling
2018-03-01
Pseudopotential lattice Boltzmann methods (LBMs) can simulate a phase transition in high-density ratio multiphase flow systems. If coupled with thermal LBMs through equation of state, they can be used to study instantaneous phase transition phenomena with a high-temperature gradient where only one set of formulations in an LBM system can handle liquid, vapor, phase transition, and heat transport. However, at lower temperatures an unrealistic spurious current at the interface introduces instability and limits its application in real flow system. In this study, we proposed new modifications to the LBM system to minimize a spurious current which enables us to study nucleation dynamic at room temperature. To demonstrate the capabilities of this approach, the thermal ejection process is modeled as one example of a complex flow system. In an inkjet printer, a thermal pulse instantly heats up the liquid in a microfluidic chamber and nucleates bubble vapor providing the pressure pulse necessary to eject droplets at high speed. Our modified method can present a more realistic model of the explosive vaporization process since it can also capture a high-temperature/density gradient at nucleation region. Thermal inkjet technology has been successfully applied for printing cells, but cells are susceptible to mechanical damage or death as they squeeze out of the nozzle head. To study cell deformation, a spring network model, representing cells, is connected to the LBM through the immersed boundary method. Looking into strain and stress distribution of a cell membrane at its most deformed state, it is found that a high stretching rate effectively increases the rupture tension. In other words, membrane deformation energy is released through creation of multiple smaller nanopores rather than big pores. Overall, concurrently simulating multiphase flow, phase transition, heat transfer, and cell deformation in one unified LB platform, we are able to provide a better insight into the
Sohrabi, Salman; Liu, Yaling
2018-03-01
Pseudopotential lattice Boltzmann methods (LBMs) can simulate a phase transition in high-density ratio multiphase flow systems. If coupled with thermal LBMs through equation of state, they can be used to study instantaneous phase transition phenomena with a high-temperature gradient where only one set of formulations in an LBM system can handle liquid, vapor, phase transition, and heat transport. However, at lower temperatures an unrealistic spurious current at the interface introduces instability and limits its application in real flow system. In this study, we proposed new modifications to the LBM system to minimize a spurious current which enables us to study nucleation dynamic at room temperature. To demonstrate the capabilities of this approach, the thermal ejection process is modeled as one example of a complex flow system. In an inkjet printer, a thermal pulse instantly heats up the liquid in a microfluidic chamber and nucleates bubble vapor providing the pressure pulse necessary to eject droplets at high speed. Our modified method can present a more realistic model of the explosive vaporization process since it can also capture a high-temperature/density gradient at nucleation region. Thermal inkjet technology has been successfully applied for printing cells, but cells are susceptible to mechanical damage or death as they squeeze out of the nozzle head. To study cell deformation, a spring network model, representing cells, is connected to the LBM through the immersed boundary method. Looking into strain and stress distribution of a cell membrane at its most deformed state, it is found that a high stretching rate effectively increases the rupture tension. In other words, membrane deformation energy is released through creation of multiple smaller nanopores rather than big pores. Overall, concurrently simulating multiphase flow, phase transition, heat transfer, and cell deformation in one unified LB platform, we are able to provide a better insight into the
Thermal-mechanical deformation modelling of soft tissues for thermal ablation.
Li, Xin; Zhong, Yongmin; Jazar, Reza; Subic, Aleksandar
2014-01-01
Modeling of thermal-induced mechanical behaviors of soft tissues is of great importance for thermal ablation. This paper presents a method by integrating the heating process with thermal-induced mechanical deformations of soft tissues for simulation and analysis of the thermal ablation process. This method combines bio-heat transfer theories, constitutive elastic material law under thermal loads as well as non-rigid motion dynamics to predict and analyze thermal-mechanical deformations of soft tissues. The 3D governing equations of thermal-mechanical soft tissue deformation are discretized by using the finite difference scheme and are subsequently solved by numerical algorithms. Experimental results show that the proposed method can effectively predict the thermal-induced mechanical behaviors of soft tissues, and can be used for the thermal ablation therapy to effectively control the delivered heat energy for cancer treatment.
Modeling online social signed networks
Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru
2018-04-01
People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.
Modeling of Thermal Barrier Coatings
Ferguson, B. L.; Petrus, G. J.; Krauss, T. M.
1992-01-01
The project examined the effectiveness of studying the creep behavior of thermal barrier coating system through the use of a general purpose, large strain finite element program, NIKE2D. Constitutive models implemented in this code were applied to simulate thermal-elastic and creep behavior. Four separate ceramic-bond coat interface geometries were examined in combination with a variety of constitutive models and material properties. The reason for focusing attention on the ceramic-bond coat interface is that prior studies have shown that cracking occurs in the ceramic near interface features which act as stress concentration points. The model conditions examined include: (1) two bond coat coefficient of thermal expansion curves; (2) the creep coefficient and creep exponent of the bond coat for steady state creep; (3) the interface geometry; and (4) the material model employed to represent the bond coat, ceramic, and superalloy base.
Rectenna thermal model development
Kadiramangalam, Murall; Alden, Adrian; Speyer, Daniel
1992-01-01
Deploying rectennas in space requires adapting existing designs developed for terrestrial applications to the space environment. One of the major issues in doing so is to understand the thermal performance of existing designs in the space environment. Toward that end, a 3D rectenna thermal model has been developed, which involves analyzing shorted rectenna elements and finite size rectenna element arrays. A shorted rectenna element is a single element whose ends are connected together by a material of negligible thermal resistance. A shorted element is a good approximation to a central element of a large array. This model has been applied to Brown's 2.45 GHz rectenna design. Results indicate that Brown's rectenna requires redesign or some means of enhancing the heat dissipation in order for the diode temperature to be maintained below 200 C above an output power density of 620 W/sq.m. The model developed in this paper is very general and can be used for the analysis and design of any type of rectenna design of any frequency.
Energy Technology Data Exchange (ETDEWEB)
Ping, Tso Chin [Malaya Univ., Kuala Lumpur (Malaysia)
1984-12-01
The phenomenon of thermal explosion arises in several important safety problems, yet scientists are still baffled by its origin. This article reviews some of the models that have been proposed to explain the phenomenon.
Statistical Models for Social Networks
Snijders, Tom A. B.; Cook, KS; Massey, DS
2011-01-01
Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For
Nonlinear thermal reduced model for Microwave Circuit Analysis
Chang, Christophe; Sommet, Raphael; Quéré, Raymond; Dueme, Ph.
2004-01-01
With the constant increase of transistor power density, electro thermal modeling is becoming a necessity for accurate prediction of device electrical performances. For this reason, this paper deals with a methodology to obtain a precise nonlinear thermal model based on Model Order Reduction of a three dimensional thermal Finite Element (FE) description. This reduced thermal model is based on the Ritz vector approach which ensure the steady state solution in every case. An equi...
Atomistic Modeling of Thermal Conductivity of Epoxy Nanotube Composites
Fasanella, Nicholas A.; Sundararaghavan, Veera
2016-05-01
The Green-Kubo method was used to investigate the thermal conductivity as a function of temperature for epoxy/single wall carbon nanotube (SWNT) nanocomposites. An epoxy network of DGEBA-DDS was built using the `dendrimer' growth approach, and conductivity was computed by taking into account long-range Coulombic forces via a k-space approach. Thermal conductivity was calculated in the direction perpendicular to, and along the SWNT axis for functionalized and pristine SWNT/epoxy nanocomposites. Inefficient phonon transport at the ends of nanotubes is an important factor in the thermal conductivity of the nanocomposites, and for this reason discontinuous nanotubes were modeled in addition to long nanotubes. The thermal conductivity of the long, pristine SWNT/epoxy system is equivalent to that of an isolated SWNT along its axis, but there was a 27% reduction perpendicular to the nanotube axis. The functionalized, long SWNT/epoxy system had a very large increase in thermal conductivity along the nanotube axis (~700%), as well as the directions perpendicular to the nanotube (64%). The discontinuous nanotubes displayed an increased thermal conductivity along the SWNT axis compared to neat epoxy (103-115% for the pristine SWNT/epoxy, and 91-103% for functionalized SWNT/epoxy system). The functionalized system also showed a 42% improvement perpendicular to the nanotube, while the pristine SWNT/epoxy system had no improvement over epoxy. The thermal conductivity tensor is averaged over all possible orientations to see the effects of randomly orientated nanotubes, and allow for experimental comparison. Excellent agreement is seen for the discontinuous, pristine SWNT/epoxy nanocomposite. These simulations demonstrate there exists a threshold of the SWNT length where the best improvement for a composite system with randomly oriented nanotubes would transition from pristine SWNTs to functionalized SWNTs.
Agent-based modeling and network dynamics
Namatame, Akira
2016-01-01
The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...
Modeling Epidemic Network Failures
DEFF Research Database (Denmark)
Ruepp, Sarah Renée; Fagertun, Anna Manolova
2013-01-01
This paper presents the implementation of a failure propagation model for transport networks when multiple failures occur resulting in an epidemic. We model the Susceptible Infected Disabled (SID) epidemic model and validate it by comparing it to analytical solutions. Furthermore, we evaluate...... the SID model’s behavior and impact on the network performance, as well as the severity of the infection spreading. The simulations are carried out in OPNET Modeler. The model provides an important input to epidemic connection recovery mechanisms, and can due to its flexibility and versatility be used...... to evaluate multiple epidemic scenarios in various network types....
International Nuclear Information System (INIS)
Tso Chin Ping
1984-01-01
The phenomenon of thermal explosion arises in several important safety problems, yet scientists are still baffled by its origin. This article reviews some of the models that have been proposed to explain the phenomenon. (author)
A nonaffine network model for elastomers undergoing finite deformations
Davidson, Jacob D.; Goulbourne, N. C.
2013-08-01
In this work, we construct a new physics-based model of rubber elasticity to capture the strain softening, strain hardening, and deformation-state dependent response of rubber materials undergoing finite deformations. This model is unique in its ability to capture large-stretch mechanical behavior with parameters that are connected to the polymer chemistry and can also be easily identified with the important characteristics of the macroscopic stress-stretch response. The microscopic picture consists of two components: a crosslinked network of Langevin chains and an entangled network with chains confined to a nonaffine tube. These represent, respectively, changes in entropy due to thermally averaged chain conformations and changes in entropy due to the magnitude of these conformational fluctuations. A simple analytical form for the strain energy density is obtained using Rubinstein and Panyukov's single-chain description of network behavior. The model only depends on three parameters that together define the initial modulus, extent of strain softening, and the onset of strain hardening. Fits to large stretch data for natural rubber, silicone rubber, VHB 4905 (polyacrylate rubber), and b186 rubber (a carbon black-filled rubber) are presented, and a comparison is made with other similar constitutive models of large-stretch rubber elasticity. We demonstrate that the proposed model provides a complete description of elastomers undergoing large deformations for different applied loading configurations. Moreover, since the strain energy is obtained using a clear set of physical assumptions, this model may be tested and used to interpret the results of computer simulation and experiments on polymers of known microscopic structure.
Current approaches to gene regulatory network modelling
Directory of Open Access Journals (Sweden)
Brazma Alvis
2007-09-01
Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.
Network Bandwidth Utilization Forecast Model on High Bandwidth Network
Energy Technology Data Exchange (ETDEWEB)
Yoo, Wucherl; Sim, Alex
2014-07-07
With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.
Network bandwidth utilization forecast model on high bandwidth networks
Energy Technology Data Exchange (ETDEWEB)
Yoo, Wuchert (William) [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sim, Alex [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2015-03-30
With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2%. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.
RMBNToolbox: random models for biochemical networks
Directory of Open Access Journals (Sweden)
Niemi Jari
2007-05-01
Full Text Available Abstract Background There is an increasing interest to model biochemical and cell biological networks, as well as to the computational analysis of these models. The development of analysis methodologies and related software is rapid in the field. However, the number of available models is still relatively small and the model sizes remain limited. The lack of kinetic information is usually the limiting factor for the construction of detailed simulation models. Results We present a computational toolbox for generating random biochemical network models which mimic real biochemical networks. The toolbox is called Random Models for Biochemical Networks. The toolbox works in the Matlab environment, and it makes it possible to generate various network structures, stoichiometries, kinetic laws for reactions, and parameters therein. The generation can be based on statistical rules and distributions, and more detailed information of real biochemical networks can be used in situations where it is known. The toolbox can be easily extended. The resulting network models can be exported in the format of Systems Biology Markup Language. Conclusion While more information is accumulating on biochemical networks, random networks can be used as an intermediate step towards their better understanding. Random networks make it possible to study the effects of various network characteristics to the overall behavior of the network. Moreover, the construction of artificial network models provides the ground truth data needed in the validation of various computational methods in the fields of parameter estimation and data analysis.
Overview of thermal conductivity models of anisotropic thermal insulation materials
Skurikhin, A. V.; Kostanovsky, A. V.
2017-11-01
Currently, the most of existing materials and substances under elaboration are anisotropic. It makes certain difficulties in the study of heat transfer process. Thermal conductivity of the materials can be characterized by tensor of the second order. Also, the parallelism between the temperature gradient vector and the density of heat flow vector is violated in anisotropic thermal insulation materials (TIM). One of the most famous TIM is a family of integrated thermal insulation refractory material («ITIRM»). The main component ensuring its properties is the «inflated» vermiculite. Natural mineral vermiculite is ground into powder state, fired by gas burner for dehydration, and its precipitate is then compressed. The key feature of thus treated batch of vermiculite is a package structure. The properties of the material lead to a slow heating of manufactured products due to low absorption and high radiation reflection. The maximum of reflection function is referred to infrared spectral region. A review of current models of heat propagation in anisotropic thermal insulation materials is carried out, as well as analysis of their thermal and optical properties. A theoretical model, which allows to determine the heat conductivity «ITIRM», can be useful in the study of thermal characteristics such as specific heat capacity, temperature conductivity, and others. Materials as «ITIRM» can be used in the metallurgy industry, thermal energy and nuclear power-engineering.
International Nuclear Information System (INIS)
Baek, Won Pil; Song, Chul Hwa; Jeong, Jae Jun; Choi, Ki Yong; Kang, Kyoung Ho
2004-07-01
1. Scope and Objectives of the Project - Successful holding of the NURETH-10 - Analysis of the international trends in technology development and applications for nuclear thermal-hydraulics - Establishment of the international cooperative network and cooperative research strategy between Korea and USA on nuclear thermal-hydraulics 2. Research Results - Successful holding of the NURETH-10 - Analysis of the international trends in technology development and applications for nuclear thermal-hydraulics: - Establishment of international cooperative network and cooperative research strategy focused between Korea and USA on nuclear thermal-hydraulics: 3. Application Plan of the Research Results - Utilization as the basic data/information in establishing the domestic R and D directions and the international cooperative research strategy, - Application of the relevant experiences and data bases of NURETH-10 for holding future international conferences, - Promote more effective and productive research cooperation between Korea and USA
Mathematical Models of IABG Thermal-Vacuum Facilities
Doring, Daniel; Ulfers, Hendrik
2014-06-01
IABG in Ottobrunn, Germany, operates thermal-vacuum facilities of different sizes and complexities as a service for space-testing of satellites and components. One aspect of these tests is the qualification of the thermal control system that keeps all onboard components within their save operating temperature band. As not all possible operation / mission states can be simulated within a sensible test time, usually a subset of important and extreme states is tested at TV facilities to validate the thermal model of the satellite, which is then used to model all other possible mission states. With advances in the precision of customer thermal models, simple assumptions of the test environment (e.g. everything black & cold, one solar constant of light from this side) are no longer sufficient, as real space simulation chambers do deviate from this ideal. For example the mechanical adapters which support the spacecraft are usually not actively cooled. To enable IABG to provide a model that is sufficiently detailed and realistic for current system tests, Munich engineering company CASE developed ESATAN models for the two larger chambers. CASE has many years of experience in thermal analysis for space-flight systems and ESATAN. The two models represent the rather simple (and therefore very homogeneous) 3m-TVA and the extremely complex space simulation test facility and its solar simulator. The cooperation of IABG and CASE built up extensive knowledge of the facilities thermal behaviour. This is the key to optimally support customers with their test campaigns in the future. The ESARAD part of the models contains all relevant information with regard to geometry (CAD data), surface properties (optical measurements) and solar irradiation for the sun simulator. The temperature of the actively cooled thermal shrouds is measured and mapped to the thermal mesh to create the temperature field in the ESATAN part as boundary conditions. Both models comprise switches to easily
Biological transportation networks: Modeling and simulation
Albi, Giacomo
2015-09-15
We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation and angiogenesis) and ion transportation networks (e.g., neural networks) is explained in detail and basic analytical features like the gradient flow structure of the fluid transportation network model and the impact of the model parameters on the geometry and topology of network formation are analyzed. We also present a numerical finite-element based discretization scheme and discuss sample cases of network formation simulations.
Thermally rearranged (TR) bismaleimide-based network polymers for gas separation membranes.
Do, Yu Seong; Lee, Won Hee; Seong, Jong Geun; Kim, Ju Sung; Wang, Ho Hyun; Doherty, Cara M; Hill, Anita J; Lee, Young Moo
2016-11-15
Highly permeable, thermally rearranged polymer membranes based on bismaleimide derivatives that exhibit excellent CO 2 permeability up to 5440 Barrer with a high BET surface area (1130 m 2 g -1 ) are reported for the first time. In addition, the membranes can be easily used to form semi-interpenetrating networks with other polymers endowing them with superior gas transport properties.
Electrical and thermal modeling of railguns
International Nuclear Information System (INIS)
Kerrisk, J.F.
1984-01-01
Electrical and thermal modeling of railguns at Los Alamos has been done for two purposes: (1) to obtain detailed information about the behavior of specific railgun components such as the rails, and (2) to predict overall performance of railgun tests. Detailed electrical and thermal modeling has concentrated on calculations of the inductance and surface current distribution of long parallel conductors in the high-frequency limit and on calculations of current and thermal diffusion in rails. Inductance calculations for various rail cross sections and for magnetic flux compression generators (MFCG) have been done. Inductance and current distribution results were compared with experimental measurements. Twodimensional calculations of current and thermal diffusion in rail cross sections have been done; predictions of rail heating and melting as a function of rail size and total current have been made. An overall performance model of a railgun and power supply has been developed and used to design tests at Los Alamos. The lumped-parameter circuit model uses results from the detailed inductance and current diffusion calculations along with other circuit component models to predict rail current and projectile acceleration, velocity, and position as a function of time
Modelling and Control of Thermal System
Directory of Open Access Journals (Sweden)
Vratislav Hladky
2014-01-01
Full Text Available Work presented here deals with the modelling of thermal processes in a thermal system consisting of direct and indirect heat exchangers. The overal thermal properties of the medium and the system itself such as liquid mixing or heat capacity are shortly analysed and their features required for modelling are reasoned and therefore simplified or neglected. Special attention is given to modelling heat losses radiated into the surroundings through the walls as they are the main issue of the effective work with the heat systems. Final part of the paper proposes several ways of controlling the individual parts’ temperatures as well as the temperature of the system considering heating elements or flowage rate as actuators.
Generalized Network Psychometrics : Combining Network and Latent Variable Models
Epskamp, S.; Rhemtulla, M.; Borsboom, D.
2017-01-01
We introduce the network model as a formal psychometric model, conceptualizing the covariance between psychometric indicators as resulting from pairwise interactions between observable variables in a network structure. This contrasts with standard psychometric models, in which the covariance between
Bayesian Network Webserver: a comprehensive tool for biological network modeling.
Ziebarth, Jesse D; Bhattacharya, Anindya; Cui, Yan
2013-11-01
The Bayesian Network Webserver (BNW) is a platform for comprehensive network modeling of systems genetics and other biological datasets. It allows users to quickly and seamlessly upload a dataset, learn the structure of the network model that best explains the data and use the model to understand relationships between network variables. Many datasets, including those used to create genetic network models, contain both discrete (e.g. genotype) and continuous (e.g. gene expression traits) variables, and BNW allows for modeling hybrid datasets. Users of BNW can incorporate prior knowledge during structure learning through an easy-to-use structural constraint interface. After structure learning, users are immediately presented with an interactive network model, which can be used to make testable hypotheses about network relationships. BNW, including a downloadable structure learning package, is available at http://compbio.uthsc.edu/BNW. (The BNW interface for adding structural constraints uses HTML5 features that are not supported by current version of Internet Explorer. We suggest using other browsers (e.g. Google Chrome or Mozilla Firefox) when accessing BNW). ycui2@uthsc.edu. Supplementary data are available at Bioinformatics online.
Eight challenges for network epidemic models
Directory of Open Access Journals (Sweden)
Lorenzo Pellis
2015-03-01
Full Text Available Networks offer a fertile framework for studying the spread of infection in human and animal populations. However, owing to the inherent high-dimensionality of networks themselves, modelling transmission through networks is mathematically and computationally challenging. Even the simplest network epidemic models present unanswered questions. Attempts to improve the practical usefulness of network models by including realistic features of contact networks and of host–pathogen biology (e.g. waning immunity have made some progress, but robust analytical results remain scarce. A more general theory is needed to understand the impact of network structure on the dynamics and control of infection. Here we identify a set of challenges that provide scope for active research in the field of network epidemic models.
Complex networks-based energy-efficient evolution model for wireless sensor networks
Energy Technology Data Exchange (ETDEWEB)
Zhu Hailin [Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, P.O. Box 106, Beijing 100876 (China)], E-mail: zhuhailin19@gmail.com; Luo Hong [Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, P.O. Box 106, Beijing 100876 (China); Peng Haipeng; Li Lixiang; Luo Qun [Information Secure Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China)
2009-08-30
Based on complex networks theory, we present two self-organized energy-efficient models for wireless sensor networks in this paper. The first model constructs the wireless sensor networks according to the connectivity and remaining energy of each sensor node, thus it can produce scale-free networks which have a performance of random error tolerance. In the second model, we not only consider the remaining energy, but also introduce the constraint of links to each node. This model can make the energy consumption of the whole network more balanced. Finally, we present the numerical experiments of the two models.
Complex networks-based energy-efficient evolution model for wireless sensor networks
International Nuclear Information System (INIS)
Zhu Hailin; Luo Hong; Peng Haipeng; Li Lixiang; Luo Qun
2009-01-01
Based on complex networks theory, we present two self-organized energy-efficient models for wireless sensor networks in this paper. The first model constructs the wireless sensor networks according to the connectivity and remaining energy of each sensor node, thus it can produce scale-free networks which have a performance of random error tolerance. In the second model, we not only consider the remaining energy, but also introduce the constraint of links to each node. This model can make the energy consumption of the whole network more balanced. Finally, we present the numerical experiments of the two models.
Brand Marketing Model on Social Networks
Directory of Open Access Journals (Sweden)
Jolita Jezukevičiūtė
2014-04-01
Full Text Available The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalysis of a single case study revealed a brand marketingsocial networking tools that affect consumers the most. Basedon information analysis and methodological studies, develop abrand marketing model on social networks.
International Nuclear Information System (INIS)
Cranwell, R.M.
1983-01-01
The Fuel Cycle Risk Analysis Division of Sandia National Laboratories has been funded by the US Nuclear Regulatory Commission to develop a methodology for use in assessing the long-term risk from the disposal of radioactive wastes in deep geologic formations. As part of this program, the Dynamic Network (DNET) model was developed to investigate waste/near field interactions associated with the disposal of radioactive wastes in bedded salt formations. The model is a quasi-multi-dimensional network model with capabilities for simulating processes such as fluid flow, heat transport, salt dissolution, salt creep, and the effects of thermal expansion and subsedence on the rock units surrounding the repository. The use of DNET has been demonstrated in the analysis of a hypothetical disposal site containing a bedded salt formation as the host medium for the repository. An example of this demonstration analysis is discussed. Furthermore, the outcome of sensitivity analyses performed on the DNET model are presented
Introducing Synchronisation in Deterministic Network Models
DEFF Research Database (Denmark)
Schiøler, Henrik; Jessen, Jan Jakob; Nielsen, Jens Frederik D.
2006-01-01
The paper addresses performance analysis for distributed real time systems through deterministic network modelling. Its main contribution is the introduction and analysis of models for synchronisation between tasks and/or network elements. Typical patterns of synchronisation are presented leading...... to the suggestion of suitable network models. An existing model for flow control is presented and an inherent weakness is revealed and remedied. Examples are given and numerically analysed through deterministic network modelling. Results are presented to highlight the properties of the suggested models...
Thermal stress management of a solid oxide fuel cell using neural network predictive control
International Nuclear Information System (INIS)
Hajimolana, S.A.; Tonekabonimoghadam, S.M.; Hussain, M.A.; Chakrabarti, M.H.; Jayakumar, N.S.; Hashim, M.A.
2013-01-01
In SOFC (solid oxide fuel cell) systems operating at high temperatures, temperature fluctuation induces a thermal stress in the electrodes and electrolyte ceramics; therefore, the cell temperature distribution is recommended to be kept as constant as possible. In the present work, a mathematical model based on first principles is presented to avert such temperature fluctuations. The fuel cell running on ammonia is divided into five subsystems and factors such as mass/energy/momentum transfer, diffusion through porous media, electrochemical reactions, and polarization losses inside the subsystems are presented. Dynamic cell-tube temperature responses of the cell to step changes in conditions of the feed streams is investigated. The results of simulation indicate that the transient response of the SOFC is mainly influenced by the temperature dynamics. It is also shown that the inlet stream temperatures are associated with the highest long term start-up time (467 s) among other parameters in terms of step changes. In contrast the step change in fuel velocity has the lowest influence on the start-up time (about 190 s from initial steady state to the new steady state) among other parameters. A NNPC (neural network predictive controller) is then implemented for thermal stress management by controlling the cell tube temperature to avoid performance degradation by manipulating the temperature of the inlet air stream. The regulatory performance of the NNPC is compared with a PI (proportional–integral) controller. The performance of the control system confirms that NNPC is a non-linear-model-based strategy which can assure less oscillating control responses with shorter settling times in comparison to the PI controller. - Highlights: • Effect of the operating parameters on the fuel cell temperature is analysed. • A neural network predictive controller (NNPC) is implemented. • The performance of NNPC is compared with the PI controller. • A detailed model is used for
Phonon model of perovskite thermal capacity
International Nuclear Information System (INIS)
Kesler, Ya.A.; Poloznikova, M.Eh.; Petrov, K.I.
1983-01-01
A model for calculating the temperature curve of thermal capacity of perovskite family crystals on the basis of vibrational spectra is proposed. Different representatives of the perovskite family: cubic SrTiO 3 , tetragonal BaTiO 3 and orthorbombic CaTiO 3 and LaCrO 3 are considered. The total frequency set is used in thermal capacity calcUlations. Comparison of the thermal capacity values of compounds calculated on the basis of the proposed model with the experimental values shows their good agreement. The method is also recommended for other compounds with the perovskite-like structure
Thermal conductivity model for nanoporous thin films
Huang, Congliang; Zhao, Xinpeng; Regner, Keith; Yang, Ronggui
2018-03-01
Nanoporous thin films have attracted great interest because of their extremely low thermal conductivity and potential applications in thin thermal insulators and thermoelectrics. Although there are some numerical and experimental studies about the thermal conductivity of nanoporous thin films, a simplified model is still needed to provide a straightforward prediction. In this paper, by including the phonon scattering lifetimes due to film thickness boundary scattering, nanopore scattering and the frequency-dependent intrinsic phonon-phonon scattering, a fitting-parameter-free model based on the kinetic theory of phonon transport is developed to predict both the in-plane and the cross-plane thermal conductivities of nanoporous thin films. With input parameters such as the lattice constants, thermal conductivity, and the group velocity of acoustic phonons of bulk silicon, our model shows a good agreement with available experimental and numerical results of nanoporous silicon thin films. It illustrates that the size effect of film thickness boundary scattering not only depends on the film thickness but also on the size of nanopores, and a larger nanopore leads to a stronger size effect of the film thickness. Our model also reveals that there are different optimal structures for getting the lowest in-plane and cross-plane thermal conductivities.
Modeling Network Interdiction Tasks
2015-09-17
118 xiii Table Page 36 Computation times for weighted, 100-node random networks for GAND Approach testing in Python ...in Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 38 Accuracy measures for weighted, 100-node random networks for GAND...networks [15:p. 1]. A common approach to modeling network interdiction is to formulate the problem in terms of a two-stage strategic game between two
Mobility Models for Next Generation Wireless Networks Ad Hoc, Vehicular and Mesh Networks
Santi, Paolo
2012-01-01
Mobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks provides the reader with an overview of mobility modelling, encompassing both theoretical and practical aspects related to the challenging mobility modelling task. It also: Provides up-to-date coverage of mobility models for next generation wireless networksOffers an in-depth discussion of the most representative mobility models for major next generation wireless network application scenarios, including WLAN/mesh networks, vehicular networks, wireless sensor networks, and
Homogenized thermal conduction model for particulate foods
Chinesta , Francisco; Torres , Rafael; Ramón , Antonio; Rodrigo , Mari Carmen; Rodrigo , Miguel
2002-01-01
International audience; This paper deals with the definition of an equivalent thermal conductivity for particulate foods. An homogenized thermal model is used to asses the effect of particulate spatial distribution and differences in thermal conductivities. We prove that the spatial average of the conductivity can be used in an homogenized heat transfer model if the conductivity differences among the food components are not very large, usually the highest conductivity ratio between the foods ...
Monitoring of Thermal Protection Systems Using Robust Self-Organizing Optical Fiber Sensing Networks
Richards, Lance
2013-01-01
The general aim of this work is to develop and demonstrate a prototype structural health monitoring system for thermal protection systems that incorporates piezoelectric acoustic emission (AE) sensors to detect the occurrence and location of damaging impacts, and an optical fiber Bragg grating (FBG) sensor network to evaluate the effect of detected damage on the thermal conductivity of the TPS material. Following detection of an impact, the TPS would be exposed to a heat source, possibly the sun, and the temperature distribution on the inner surface in the vicinity of the impact measured by the FBG network. A similar procedure could also be carried out as a screening test immediately prior to re-entry. The implications of any detected anomalies in the measured temperature distribution will be evaluated for their significance in relation to the performance of the TPS during re-entry. Such a robust TPS health monitoring system would ensure overall crew safety throughout the mission, especially during reentry
Complex Networks in Psychological Models
Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.
We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.
Thermal modelling of friction stir welding
DEFF Research Database (Denmark)
Schmidt, Henrik Nikolaj Blicher; Hattel, Jesper Henri
2008-01-01
The objective of the present work is to present the basic elements of the thermal modelling of friction stir welding as well as to clarify some of the uncertainties in the literature regarding the different contributions to the heat generation. Some results from a new thermal pseudomechanical model...... in which the temperature-dependent yield stress of the weld material controls the heat generation are also presented....
Thermal margin model for transition core of KSNP
International Nuclear Information System (INIS)
Nahm, Kee Yil; Lim, Jong Seon; Park, Sung Kew; Chun, Chong Kuk; Hwang, Sun Tack
2004-01-01
The PLUS7 fuel was developed with mixing vane grids for KSNP. For the transition core partly loaded with the PLUS7 fuels, the procedure to set up the optimum thermal margin model of the transition core was suggested by introducing AOPM concept into the screening method which determines the limiting assembly. According to the procedure, the optimum thermal margin model of the first transition core was set up by using a part of nuclear data for the first transition and the homogeneous core with PLUS7 fuels. The generic thermal margin model of PLUS7 fuel was generated with the AOPM of 138%. The overpower penalties on the first transition core were calculated to be 1.0 and 0.98 on the limiting assembly and the generic thermal margin model, respectively. It is not usual case to impose the overpower penalty on reload cores. It is considered that the lack of channel flow due to the difference of pressure drop between PLUS7 and STD fuels results in the decrease of DNBR. The AOPM of the first transition core is evaluated to be about 135% by using the optimum generic thermal margin model which involves the generic thermal margin model and the total overpower penalty. The STD fuel is not included among limiting assembly candidates in the second transition core, because they have much lower pin power than PLUS7 fuels. The reduced number of STD fuels near the limiting assembly candidates the flow from the limiting assembly to increase the thermal margin for the second transition core. It is expected that cycle specific overpower penalties increase the thermal margin for the transition core. Using the procedure to set up the optimum thermal margin model makes sure that the enhanced thermal margin of PLUS7 fuel can be sufficiently applied to not only the homogeneous core but also the transition core
McKim, Stephen A.
2016-01-01
This thesis describes the development and test data validation of the thermal model that is the foundation of a thermal capacitance spacecraft propellant load estimator. Specific details of creating the thermal model for the diaphragm propellant tank used on NASA's Magnetospheric Multiscale spacecraft using ANSYS and the correlation process implemented to validate the model are presented. The thermal model was correlated to within plus or minus 3 degrees Centigrade of the thermal vacuum test data, and was found to be relatively insensitive to uncertainties in applied heat flux and mass knowledge of the tank. More work is needed, however, to refine the thermal model to further improve temperature predictions in the upper hemisphere of the propellant tank. Temperatures predictions in this portion were found to be 2-2.5 degrees Centigrade lower than the test data. A road map to apply the model to predict propellant loads on the actual MMS spacecraft toward its end of life in 2017-2018 is also presented.
Model-based analysis of thermal insulation coatings
DEFF Research Database (Denmark)
Kiil, Søren
2014-01-01
Thermal insulation properties of coatings based on selected functional filler materials are investigated. The underlying physics, thermal conductivity of a heterogeneous two-component coating, and porosity and thermal conductivity of hollow spheres (HS) are quantified and a mathematical model for...
Artificial neural network modelling
Samarasinghe, Sandhya
2016-01-01
This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .
The Lattice and Thermal Radiation Conductivity of Thermal Barrier Coatings: Models and Experiments
Zhu, Dongming; Spuckler, Charles M.
2010-01-01
The lattice and radiation conductivity of ZrO2-Y2O3 thermal barrier coatings was evaluated using a laser heat flux approach. A diffusion model has been established to correlate the coating apparent thermal conductivity to the lattice and radiation conductivity. The radiation conductivity component can be expressed as a function of temperature, coating material scattering, and absorption properties. High temperature scattering and absorption of the coating systems can be also derived based on the testing results using the modeling approach. A comparison has been made for the gray and nongray coating models in the plasma-sprayed thermal barrier coatings. The model prediction is found to have a good agreement with experimental observations.
International Nuclear Information System (INIS)
Beck, T.; Bieler, A.; Thomas, N.
2012-01-01
We present structural and thermal model (STM) tests of the BepiColombo laser altimeter (BELA) receiver baffle with emphasis on the correlation of the data with a thermal mathematical model. The test unit is a part of the thermal and optical protection of the BELA instrument being tested under infrared and solar irradiation at University of Bern. An iterative optimization method known as particle swarm optimization has been adapted to adjust the model parameters, mainly the linear conductivity, in such a way that model and test results match. The thermal model reproduces the thermal tests to an accuracy of 4.2 °C ± 3.2 °C in a temperature range of 200 °C after using only 600 iteration steps of the correlation algorithm. The use of this method brings major benefits to the accuracy of the results as well as to the computational time required for the correlation. - Highlights: ► We present model correlations of the BELA receiver baffle to thermal balance tests. ► Adaptive particle swarm optimization has been adapted for the correlation. ► The method improves the accuracy of the correlation and the computational time.
Directory of Open Access Journals (Sweden)
E.M. Matos
2002-07-01
Full Text Available This work presents a model to predict the behavior of velocity, gas holdup and local concentration fields in a pseudo-two-phase gas-liquid column reactor applied for thermal hydrocracking of petroleum heavy fractions. The model is based on the momentum and mass balances for the system, using an Eulerian-Eulerian approach. Using the k-epsilon model,fluid dynamics accounts for both laminar and turbulent flows, with discrete small bubbles (hydrogen flowing in a continuous pseudohomogeneous liquid phase (oil and catalyst particles. The petroleum is assumed to be a mixture of pseudocomponents, grouped by similar chemical structural properties, and the thermal hydrocracking is taken into account using a kinetic network based on these pseudocomponents.
El-Sa'Ad, Leila
1989-12-01
Available from UMI in association with The British Library. Requires signed TDF. Epoxy resins exhibit many desirable properties which make them ideal subjects for use as matrices of composite materials in many commercial, military and space applications. However, due to their high cross-link density they are often brittle. Epoxy resin networks have been modified by incorporating tough, ductile thermoplastics. Such systems are referred to as Semi-Interpenetrating Polymer Networks (Semi-IPN). Systematic modification to the thermoplastics backbone allowed the morphology of the blend to be controlled from a homogeneous one-phase structure to fully separated structures. The moisture absorption by composites in humid environments has been found to lead to a deterioration in the physical and mechanical properties of the matrix. Therefore, in order to utilize composites to their full potential, their response to hot/wet environments must be known. The aims of this investigation were two-fold. Firstly, to study the effect of varying the temperature of exposure at different stages in the absorption process on the water absorption behaviour of a TGDDM/DDS epoxy resin system. Secondly, to study water absorption characteristics, under isothermal conditions, of Semi-Interpenetrating Polymer Networks possessing different morphologies, and develop a theoretical model to evaluate the diffusion coefficients of the two-phase structures. The mathematical treatment used in this analysis was based on Fick's second law of diffusion. Tests were performed on specimens immersed in water at 10 ^circ, 40^circ and 70^circC, their absorption behaviour and swelling behaviour, as a consequence of water absorption, were investigated. The absorption results of the variable temperature absorption tests indicated a saturation dependence on the absorption behaviour. Specimens saturated at a high temperature will undergo further absorption when transferred to a lower temperature. This behaviour was
Gossip spread in social network Models
Johansson, Tobias
2017-04-01
Gossip almost inevitably arises in real social networks. In this article we investigate the relationship between the number of friends of a person and limits on how far gossip about that person can spread in the network. How far gossip travels in a network depends on two sets of factors: (a) factors determining gossip transmission from one person to the next and (b) factors determining network topology. For a simple model where gossip is spread among people who know the victim it is known that a standard scale-free network model produces a non-monotonic relationship between number of friends and expected relative spread of gossip, a pattern that is also observed in real networks (Lind et al., 2007). Here, we study gossip spread in two social network models (Toivonen et al., 2006; Vázquez, 2003) by exploring the parameter space of both models and fitting them to a real Facebook data set. Both models can produce the non-monotonic relationship of real networks more accurately than a standard scale-free model while also exhibiting more realistic variability in gossip spread. Of the two models, the one given in Vázquez (2003) best captures both the expected values and variability of gossip spread.
Quantifying the relevance of adaptive thermal comfort models in moderate thermal climate zones
Energy Technology Data Exchange (ETDEWEB)
Hoof, Joost van; Hensen, Jan L.M. [Faculty of Architecture, Building and Planning, Technische Universiteit Eindhoven, Vertigo 6.18, P.O. Box 513, 5600 MB Eindhoven (Netherlands)
2007-01-15
Standards governing thermal comfort evaluation are on a constant cycle of revision and public review. One of the main topics being discussed in the latest round was the introduction of an adaptive thermal comfort model, which now forms an optional part of ASHRAE Standard 55. Also on a national level, adaptive thermal comfort guidelines come into being, such as in the Netherlands. This paper discusses two implementations of the adaptive comfort model in terms of usability and energy use for moderate maritime climate zones by means of literature study, a case study comprising temperature measurements, and building performance simulation. It is concluded that for moderate climate zones the adaptive model is only applicable during summer months, and can reduce energy for naturally conditioned buildings. However, the adaptive thermal comfort model has very limited application potential for such climates. Additionally we suggest a temperature parameter with a gradual course to replace the mean monthly outdoor air temperature to avoid step changes in optimum comfort temperatures. (author)
Liu, Feifei; Lan, Fengchong; Chen, Jiqing
2016-07-01
Heat pipe cooling for battery thermal management systems (BTMSs) in electric vehicles (EVs) is growing due to its advantages of high cooling efficiency, compact structure and flexible geometry. Considering the transient conduction, phase change and uncertain thermal conditions in a heat pipe, it is challenging to obtain the dynamic thermal characteristics accurately in such complex heat and mass transfer process. In this paper, a ;segmented; thermal resistance model of a heat pipe is proposed based on thermal circuit method. The equivalent conductivities of different segments, viz. the evaporator and condenser of pipe, are used to determine their own thermal parameters and conditions integrated into the thermal model of battery for a complete three-dimensional (3D) computational fluid dynamics (CFD) simulation. The proposed ;segmented; model shows more precise than the ;non-segmented; model by the comparison of simulated and experimental temperature distribution and variation of an ultra-thin micro heat pipe (UMHP) battery pack, and has less calculation error to obtain dynamic thermal behavior for exact thermal design, management and control of heat pipe BTMSs. Using the ;segmented; model, the cooling effect of the UMHP pack with different natural/forced convection and arrangements is predicted, and the results correspond well to the tests.
Thermal expansion and its impacts on thermal transport in the FPU-α-β model
Directory of Open Access Journals (Sweden)
Xiaodong Cao
2015-05-01
Full Text Available We study the impacts of thermal expansion, arising from the asymmetric interparticle potential, on thermal conductance in the FPU-α-β model. A nonmonotonic dependence of the temperature gradient and thermal conductance on the cubic interaction parameter α are shown, which corresponds to the variation of the coefficient of thermal expansion. Three domains with respect to α can be identified. The results are explained based on the detailed analysis of the asymmetry of the interparticle potential. The self-consistent phonon theory, which can capture the effect of thermal expansion, is developed to support our explanation in a quantitative way. Our result would be helpful to understand the issue that whether there exist normal thermal conduction in the FPU-α-β model.
DEFF Research Database (Denmark)
Bahman, Amir Sajjad; Ma, Ke; Blaabjerg, Frede
2015-01-01
accurate temperature estimation either vertically or horizontally inside the power devices is still hard to identify. This paper investigates the thermal behavior of high power module in various operating conditions by means of Finite Element Method (FEM). A novel 3D thermal impedance network considering......Thermal management of power electronic devices is essential for reliable performance especially at high power levels. One of the most important activities in the thermal management and reliability improvement is acquiring the temperature information in critical points of the power module. However...
Energy Technology Data Exchange (ETDEWEB)
Vukelja, P.I.; Naumov, R.M.; Drobnjak, G.V.; Mrvic, J.D. [Nikola Tesla Inst., Belgrade (Yugoslavia)
1996-12-31
The paper presents the results of experimental investigations of overvoltages on 6kV isolated neutral station service cable networks of thermal power plants. The overvoltages were recorded with capacitive voltage measurement systems made at the Nikola Tesla Institute. Wideband capacitive voltage measurement systems recorded a flat response from below power frequencies to 10MHz. Investigations of overvoltages were performed for appearance and interruption of metal earth faults, intermittent earth faults, switching operation of HV motors switchgear, switching operation of transformers switchgear, and transfer of the network supply from one transformer to another. On the basis of these investigations, certain measures are proposed for limiting overvoltages and for the reliability of station service of thermal power plants.
Akhmetova, I. G.; Chichirova, N. D.
2017-11-01
Currently the actual problem is a precise definition of the normative and actual heat loss. Existing methods - experimental, on metering devices, on the basis of mathematical modeling methods are not without drawbacks. Heat losses establishing during the heat carrier transport has an impact on the tariff structure of heat supply organizations. This quantity determination also promotes proper choice of main and auxiliary equipment power, temperature chart of heat supply networks, as well as the heating system structure choice with the decentralization. Calculation of actual heat loss and their comparison with standard values justifies the performance of works on improvement of the heat networks with the replacement of piping or its insulation. To determine the cause of discrepancies between normative and actual heat losses thermal tests on the magnitude of the actual heat losses in the 124 sections of heat networks in Kazan. As were carried out the result mathematical model of the regulatory definition of heat losses is developed and tested. This model differ from differs the existing according the piping insulation type. The application of this factor will bring the value of calculative normative losses heat energy to their actual value. It is of great importance for enterprises operating distribution networks and because of the conditions of their configuration and extensions do not have the technical ability to produce thermal testing.
Brand Marketing Model on Social Networks
Jolita Jezukevičiūtė; Vida Davidavičienė
2014-01-01
The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalys...
Energy Technology Data Exchange (ETDEWEB)
Band, D.L.
1986-12-01
The infrared, optical and x-ray continua from radio quiet active galactic nuclei (AGN) are explained by a compact non-thermal source surrounding a thermal ultraviolet emitter, presumably the accretion disk around a supermassive black hole. The ultraviolet source is observed as the ''big blue bump.'' The flat (..cap alpha.. approx. = .7) hard x-ray spectrum results from the scattering of thermal ultraviolet photons by the flat, low energy end of an electron distribution ''broken'' by Compton losses; the infrared through soft x-ray continuum is the synchrotron radiation of the steep, high energy end of the electron distribution. Quantitative fits to specific AGN result in models which satisfy the variability constraints but require electron (re)acceleration throughout the source. 11 refs., 1 fig.
A model of coauthorship networks
Zhou, Guochang; Li, Jianping; Xie, Zonglin
2017-10-01
A natural way of representing the coauthorship of authors is to use a generalization of graphs known as hypergraphs. A random geometric hypergraph model is proposed here to model coauthorship networks, which is generated by placing nodes on a region of Euclidean space randomly and uniformly, and connecting some nodes if the nodes satisfy particular geometric conditions. Two kinds of geometric conditions are designed to model the collaboration patterns of academic authorities and basic researches respectively. The conditions give geometric expressions of two causes of coauthorship: the authority and similarity of authors. By simulation and calculus, we show that the forepart of the degree distribution of the network generated by the model is mixture Poissonian, and the tail is power-law, which are similar to these of some coauthorship networks. Further, we show more similarities between the generated network and real coauthorship networks: the distribution of cardinalities of hyperedges, high clustering coefficient, assortativity, and small-world property
In-situ measurements of material thermal parameters for accurate LED lamp thermal modelling
Vellvehi, M.; Perpina, X.; Jorda, X.; Werkhoven, R.J.; Kunen, J.M.G.; Jakovenko, J.; Bancken, P.; Bolt, P.J.
2013-01-01
This work deals with the extraction of key thermal parameters for accurate thermal modelling of LED lamps: air exchange coefficient around the lamp, emissivity and thermal conductivity of all lamp parts. As a case study, an 8W retrofit lamp is presented. To assess simulation results, temperature is
Brand marketing model on social networks
Jezukevičiūtė, Jolita; Davidavičienė, Vida
2014-01-01
Paper analyzes the brand and its marketing solutions on social networks. This analysis led to the creation of improved brand marketing model on social networks, which will contribute to the rapid and cheap organization brand recognition, increase competitive advantage and enhance consumer loyalty. Therefore, the brand and a variety of social networks are becoming a hot research area for brand marketing model on social networks. The world‘s most successful brand marketing models exploratory an...
Thermal Models of the Niger Delta: Implications for Charge Modelling
International Nuclear Information System (INIS)
Ejedawe, J.
2002-01-01
There are generally three main sources of temperature data-BHT data from log headers, production temperature data, and continuo's temperature logs. Analysis of continuous temperature profiles of over 100 wells in the Niger Delta two main thermal models (single leg and dogleg) are defined with occasional occurrence of a modified dogleg model.The dogleg model is characterised by a shallow interval of low geothermal gradient ( 3.0.C/100m). This is characteristically developed onshore area is simple, requiring only consideration of heat transients, modelling in the onshore require modelling programmes with built in modules to handle convective heat flow dissipation in the shallow layer. Current work around methods would involve tweaking of thermal conductivity values to mimic the underlying heat flow process effects, or heat flow mapping above and below the depth of gradient change. These methods allow for more realistic thermal modelling, hydrocarbon type prediction, and also more accurate prediction of temperature prior to drilling and for reservoir rock properties. The regional distribution of the models also impact on regional hydrocarbon distribution pattern in the Niger Delta
Coupled electrochemical thermal modelling of a novel Li-ion battery pack thermal management system
International Nuclear Information System (INIS)
Basu, Suman; Hariharan, Krishnan S.; Kolake, Subramanya Mayya; Song, Taewon; Sohn, Dong Kee; Yeo, Taejung
2016-01-01
Highlights: • Three-dimensional electrochemical thermal model of Li-ion battery pack using computational fluid dynamics (CFD). • Novel pack design for compact liquid cooling based thermal management system. • Simple temperature estimation algorithm for the cells in the pack using the results from the model. • Sensitivity of the thermal performance to contact resistance has been investigated. - Abstract: Thermal management system is of critical importance for a Li-ion battery pack, as high performance and long battery pack life can be simultaneously achieved when operated within a narrow range of temperature around the room temperature. An efficient thermal management system is required to keep the battery temperature in this range, despite widely varying operating conditions. A novel liquid coolant based thermal management system, for 18,650 battery pack has been introduced herein. This system is designed to be compact and economical without compromising safety. A coupled three-dimensional (3D) electrochemical thermal model is constructed for the proposed Li-ion battery pack. The model is used to evaluate the effects of different operating conditions like coolant flow-rate and discharge current on the pack temperature. Contact resistance is found to have the strongest impact on the thermal performance of the pack. From the numerical solution, a simple and novel temperature correlation of predicting the temperatures of all the individual cells given the temperature measurement of one cell is devised and validated with experimental results. Such coefficients have great potential of reducing the sensor requirement and complexity in a large Li-ion battery pack, typical of an electric vehicle.
Model Comparison for Electron Thermal Transport
Moses, Gregory; Chenhall, Jeffrey; Cao, Duc; Delettrez, Jacques
2015-11-01
Four electron thermal transport models are compared for their ability to accurately and efficiently model non-local behavior in ICF simulations. Goncharov's transport model has accurately predicted shock timing in implosion simulations but is computationally slow and limited to 1D. The iSNB (implicit Schurtz Nicolai Busquet electron thermal transport method of Cao et al. uses multigroup diffusion to speed up the calculation. Chenhall has expanded upon the iSNB diffusion model to a higher order simplified P3 approximation and a Monte Carlo transport model, to bridge the gap between the iSNB and Goncharov models while maintaining computational efficiency. Comparisons of the above models for several test problems will be presented. This work was supported by Sandia National Laboratory - Albuquerque and the University of Rochester Laboratory for Laser Energetics.
Application of neural network technology to nuclear plant thermal efficiency improvement
International Nuclear Information System (INIS)
Doremus, Rick; Allen Ho, S.; Bailey, James V.; Roman, Harry
2004-01-01
Due to the tremendous cost of building new nuclear power plants, it has become increasingly attractive to increase the power output from the existing operating power plants. There are two options that may be available to accomplish this goal. One option is to uprate the plant through licensing modification for a comfortably achievable goal of 4% to 6%. However, the licensing efforts required are no small task, vary from plant to plant, and may take years to accomplish. Some nuclear power plants may not have this option because of design, environmental, political, or geographical limitations. A second option exists that is simpler and more immediate. It focuses on improving the plant operating conditions using adaptive software that could increase the total plant output by approximately one-half percent by adjusting certain key operating parameters. No design basis analyses, hardware modifications, or licensing changes are required. In fact, this technique can be used on a plant that has already obtained licensing modification to obtain an additional one-half percent on top of the 4% to 6% increase. Public Service Electric and Gas and ARD Corporation are jointly investigating the creation of a Plant Optimization System, called POSITIVE. POSITIVE is an adaptive software tool that enables a user to analyze current plant data to identify potential problem areas and to obtain recommendations for increasing the plant's electric output. POSITIVE uses a combination of expert systems and adaptive software to analyze the thermal performance of a nuclear power plant. Historical data, obtained while the plant was above 93% power, is used to train neural networks to determine the current electric output of the plant. Once sufficiently trained, new data can be processed through the neural network. The neural network first determines the electric output associated with the current data. If the actual power matches the power predicted by the network, the neural network can be used
Target-Centric Network Modeling
DEFF Research Database (Denmark)
Mitchell, Dr. William L.; Clark, Dr. Robert M.
In Target-Centric Network Modeling: Case Studies in Analyzing Complex Intelligence Issues, authors Robert Clark and William Mitchell take an entirely new approach to teaching intelligence analysis. Unlike any other book on the market, it offers case study scenarios using actual intelligence...... reporting formats, along with a tested process that facilitates the production of a wide range of analytical products for civilian, military, and hybrid intelligence environments. Readers will learn how to perform the specific actions of problem definition modeling, target network modeling......, and collaborative sharing in the process of creating a high-quality, actionable intelligence product. The case studies reflect the complexity of twenty-first century intelligence issues by dealing with multi-layered target networks that cut across political, economic, social, technological, and military issues...
A Complex Network Approach to Distributional Semantic Models.
Directory of Open Access Journals (Sweden)
Akira Utsumi
Full Text Available A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models.
QSAR modelling using combined simple competitive learning networks and RBF neural networks.
Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E
2018-04-01
The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.
Adaptive thermal modeling of Li-ion batteries
International Nuclear Information System (INIS)
Shadman Rad, M.; Danilov, D.L.; Baghalha, M.; Kazemeini, M.; Notten, P.H.L.
2013-01-01
Highlights: • A simple, accurate and adaptive thermal model is proposed for Li-ion batteries. • Equilibrium voltages, overpotentials and entropy changes are quantified from experimental results. • Entropy changes are highly dependent on the battery State-of-Charge. • Good agreement between simulated and measured heat development is obtained under all conditions. • Radiation contributes to about 50% of heat dissipation at elevated temperatures. -- Abstract: An accurate thermal model to predict the heat generation in rechargeable batteries is an essential tool for advanced thermal management in high power applications, such as electric vehicles. For such applications, the battery materials’ details and cell design are normally not provided. In this work a simple, though accurate, thermal model for batteries has been developed, considering the temperature- and current-dependent overpotential heat generation and State-of-Charge dependent entropy contributions. High power rechargeable Li-ion (7.5 Ah) batteries have been experimentally investigated and the results are used for model verification. It is shown that the State-of-Charge dependent entropy is a significant heat source and is therefore essential to correctly predict the thermal behavior of Li-ion batteries under a wide variety of operating conditions. An adaptive model is introduced to obtain these entropy values. A temperature-dependent equation for heat transfer to the environment is also taken into account. Good agreement between the simulations and measurements is obtained in all cases. The parameters for both the heat generation and heat transfer processes can be applied to the thermal design of advanced battery packs. The proposed methodology is generic and independent on the cell chemistry and battery design. The parameters for the adaptive model can be determined by performing simple cell potential/current and temperature measurements for a limited number of charge/discharge cycles
Modeling Renewable Penertration Using a Network Economic Model
Lamont, A.
2001-03-01
This paper evaluates the accuracy of a network economic modeling approach in designing energy systems having renewable and conventional generators. The network approach models the system as a network of processes such as demands, generators, markets, and resources. The model reaches a solution by exchanging prices and quantity information between the nodes of the system. This formulation is very flexible and takes very little time to build and modify models. This paper reports an experiment designing a system with photovoltaic and base and peak fossil generators. The level of PV penetration as a function of its price and the capacities of the fossil generators were determined using the network approach and using an exact, analytic approach. It is found that the two methods agree very closely in terms of the optimal capacities and are nearly identical in terms of annual system costs.
Prediction of thermal conductivity of rock through physico-mechanical properties
Energy Technology Data Exchange (ETDEWEB)
Singh, T.N. [Department of Earth Sciences, Indian Institute of Technology, Bombay 400 076 (India); Sinha, S.; Singh, V.K. [Institute of Technology, Banaras Hindu University, Varanasi 221 005 (India)
2007-01-15
The transfer of energy between two adjacent parts of rock mainly depends on its thermal conductivity. Present study supports the use of artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS) in the study of thermal conductivity along with other intrinsic properties of rock due to its increasing importance in many areas of rock engineering, agronomy and geo environmental engineering field. In recent years, considerable effort has been made to develop techniques to determine these properties. Comparative analysis is made to analyze the capabilities among six different models of ANN and ANFIS. ANN models are based on feedforward backpropagation network with training functions resilient backpropagation (RP), one step secant (OSS) and Powell-Beale restarts (CGB) and radial basis with training functions generalized regression neural network (GRNN) and more efficient design radial basis network (NEWRB). A data set of 136 has been used for training different models and 15 were used for testing purposes. A statistical analysis is made to show the consistency among them. ANFIS is proved to be the best among all the networks tried in this case with average absolute percentage error of 0.03% and regression coefficient of 1, whereas best performance shown by the FFBP (RP) with average absolute error of 2.26%. Thermal conductivity is predicted using P-wave velocity, porosity, bulk density, uniaxial compressive strength of rock as input parameters. (author)
Monowar, Muhammad Mostafa; Bajaber, Fuad
2015-01-01
In this paper, we address the thermal rise and Quality-of-Service (QoS) provisioning issue for an intra-body Wireless Body Area Network (WBAN) having in-vivo sensor nodes. We propose a thermal-aware QoS routing protocol, called TLQoS, that facilitates the system in achieving desired QoS in terms of delay and reliability for diverse traffic types, as well as avoids the formation of highly heated nodes known as hotspot(s), and keeps the temperature rise along the network to an acceptable level....
An evolving network model with community structure
International Nuclear Information System (INIS)
Li Chunguang; Maini, Philip K
2005-01-01
Many social and biological networks consist of communities-groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties
International Nuclear Information System (INIS)
Back, Paer-Erik; Sundberg, Jan
2007-09-01
This report presents a strategy for describing, predicting and visualising the thermal aspects of the site descriptive model. The strategy is an updated version of an earlier strategy applied in all SDM versions during the initial site investigation phase at the Forsmark and Oskarshamn areas. The previous methodology for thermal modelling did not take the spatial correlation fully into account during simulation. The result was that the variability of thermal conductivity in the rock mass was not sufficiently well described. Experience from earlier thermal SDMs indicated that development of the methodology was required in order describe the spatial distribution of thermal conductivity in the rock mass in a sufficiently reliable way, taking both variability within rock types and between rock types into account. A good description of the thermal conductivity distribution is especially important for the lower tail. This tail is important for the design of a repository because it affects the canister spacing. The presented approach is developed to be used for final SDM regarding thermal properties, primarily thermal conductivity. Specific objectives for the strategy of thermal stochastic modelling are: Description: statistical description of the thermal conductivity of a rock domain. Prediction: prediction of thermal conductivity in a specific rock volume. Visualisation: visualisation of the spatial distribution of thermal conductivity. The thermal site descriptive model should include the temperature distribution and thermal properties of the rock mass. The temperature is the result of the thermal processes in the repository area. Determination of thermal transport properties can be made using different methods, such as laboratory investigations, field measurements, modelling from mineralogical composition and distribution, modelling from density logging and modelling from temperature logging. The different types of data represent different scales, which has to be
Energy Technology Data Exchange (ETDEWEB)
Back, Paer-Erik; Sundberg, Jan [Geo Innova AB (Sweden)
2007-09-15
This report presents a strategy for describing, predicting and visualising the thermal aspects of the site descriptive model. The strategy is an updated version of an earlier strategy applied in all SDM versions during the initial site investigation phase at the Forsmark and Oskarshamn areas. The previous methodology for thermal modelling did not take the spatial correlation fully into account during simulation. The result was that the variability of thermal conductivity in the rock mass was not sufficiently well described. Experience from earlier thermal SDMs indicated that development of the methodology was required in order describe the spatial distribution of thermal conductivity in the rock mass in a sufficiently reliable way, taking both variability within rock types and between rock types into account. A good description of the thermal conductivity distribution is especially important for the lower tail. This tail is important for the design of a repository because it affects the canister spacing. The presented approach is developed to be used for final SDM regarding thermal properties, primarily thermal conductivity. Specific objectives for the strategy of thermal stochastic modelling are: Description: statistical description of the thermal conductivity of a rock domain. Prediction: prediction of thermal conductivity in a specific rock volume. Visualisation: visualisation of the spatial distribution of thermal conductivity. The thermal site descriptive model should include the temperature distribution and thermal properties of the rock mass. The temperature is the result of the thermal processes in the repository area. Determination of thermal transport properties can be made using different methods, such as laboratory investigations, field measurements, modelling from mineralogical composition and distribution, modelling from density logging and modelling from temperature logging. The different types of data represent different scales, which has to be
Multilevel method for modeling large-scale networks.
Energy Technology Data Exchange (ETDEWEB)
Safro, I. M. (Mathematics and Computer Science)
2012-02-24
Understanding the behavior of real complex networks is of great theoretical and practical significance. It includes developing accurate artificial models whose topological properties are similar to the real networks, generating the artificial networks at different scales under special conditions, investigating a network dynamics, reconstructing missing data, predicting network response, detecting anomalies and other tasks. Network generation, reconstruction, and prediction of its future topology are central issues of this field. In this project, we address the questions related to the understanding of the network modeling, investigating its structure and properties, and generating artificial networks. Most of the modern network generation methods are based either on various random graph models (reinforced by a set of properties such as power law distribution of node degrees, graph diameter, and number of triangles) or on the principle of replicating an existing model with elements of randomization such as R-MAT generator and Kronecker product modeling. Hierarchical models operate at different levels of network hierarchy but with the same finest elements of the network. However, in many cases the methods that include randomization and replication elements on the finest relationships between network nodes and modeling that addresses the problem of preserving a set of simplified properties do not fit accurately enough the real networks. Among the unsatisfactory features are numerically inadequate results, non-stability of algorithms on real (artificial) data, that have been tested on artificial (real) data, and incorrect behavior at different scales. One reason is that randomization and replication of existing structures can create conflicts between fine and coarse scales of the real network geometry. Moreover, the randomization and satisfying of some attribute at the same time can abolish those topological attributes that have been undefined or hidden from
Research on the model of home networking
Yun, Xiang; Feng, Xiancheng
2007-11-01
It is the research hotspot of current broadband network to combine voice service, data service and broadband audio-video service by IP protocol to transport various real time and mutual services to terminal users (home). Home Networking is a new kind of network and application technology which can provide various services. Home networking is called as Digital Home Network. It means that PC, home entertainment equipment, home appliances, Home wirings, security, illumination system were communicated with each other by some composing network technology, constitute a networking internal home, and connect with WAN by home gateway. It is a new network technology and application technology, and can provide many kinds of services inside home or between homes. Currently, home networking can be divided into three kinds: Information equipment, Home appliances, Communication equipment. Equipment inside home networking can exchange information with outer networking by home gateway, this information communication is bidirectional, user can get information and service which provided by public networking by using home networking internal equipment through home gateway connecting public network, meantime, also can get information and resource to control the internal equipment which provided by home networking internal equipment. Based on the general network model of home networking, there are four functional entities inside home networking: HA, HB, HC, and HD. (1) HA (Home Access) - home networking connects function entity; (2) HB (Home Bridge) Home networking bridge connects function entity; (3) HC (Home Client) - Home networking client function entity; (4) HD (Home Device) - decoder function entity. There are many physical ways to implement four function entities. Based on theses four functional entities, there are reference model of physical layer, reference model of link layer, reference model of IP layer and application reference model of high layer. In the future home network
Thermal model of attic systems with radiant barriers
Energy Technology Data Exchange (ETDEWEB)
Wilkes, K.E.
1991-07-01
This report summarizes the first phase of a project to model the thermal performance of radiant barriers. The objective of this phase of the project was to develop a refined model for the thermal performance of residential house attics, with and without radiant barriers, and to verify the model by comparing its predictions against selected existing experimental thermal performance data. Models for the thermal performance of attics with and without radiant barriers have been developed and implemented on an IBM PC/AT computer. The validity of the models has been tested by comparing their predictions with ceiling heat fluxes measured in a number of laboratory and field experiments on attics with and without radiant barriers. Cumulative heat flows predicted by the models were usually within about 5 to 10 percent of measured values. In future phases of the project, the models for attic/radiant barrier performance will be coupled with a whole-house model and further comparisons with experimental data will be made. Following this, the models will be utilized to provide an initial assessment of the energy savings potential of radiant barriers in various configurations and under various climatic conditions. 38 refs., 14 figs., 22 tabs.
Energy Technology Data Exchange (ETDEWEB)
Buscheck, T., LLNL
1998-04-29
This chapter describes the physical processes and natural and engineered system conditions that affect thermal-hydrological (T-H) behavior in the unsaturated zone (UZ) at Yucca Mountain and how these effects are represented in mathematical and numerical models that are used to predict T-H conditions in the near field, altered zone, and engineered barrier system (EBS), and on waste package (WP) surfaces.
Network models in economics and finance
Pardalos, Panos; Rassias, Themistocles
2014-01-01
Using network models to investigate the interconnectivity in modern economic systems allows researchers to better understand and explain some economic phenomena. This volume presents contributions by known experts and active researchers in economic and financial network modeling. Readers are provided with an understanding of the latest advances in network analysis as applied to economics, finance, corporate governance, and investments. Moreover, recent advances in market network analysis that focus on influential techniques for market graph analysis are also examined. Young researchers will find this volume particularly useful in facilitating their introduction to this new and fascinating field. Professionals in economics, financial management, various technologies, and network analysis, will find the network models presented in this book beneficial in analyzing the interconnectivity in modern economic systems.
Context. Thermally diverse habitats may afford fish protection from climate change by providing opportunities to behaviorally optimize growing conditions. However, it is unclear what role the spatial properties of river networks will play in determining risk. Objectives. We hypot...
Complex networks under dynamic repair model
Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao
2018-01-01
Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.
Transmutation Fuel Performance Code Thermal Model Verification
Energy Technology Data Exchange (ETDEWEB)
Gregory K. Miller; Pavel G. Medvedev
2007-09-01
FRAPCON fuel performance code is being modified to be able to model performance of the nuclear fuels of interest to the Global Nuclear Energy Partnership (GNEP). The present report documents the effort for verification of the FRAPCON thermal model. It was found that, with minor modifications, FRAPCON thermal model temperature calculation agrees with that of the commercial software ABAQUS (Version 6.4-4). This report outlines the methodology of the verification, code input, and calculation results.
Thermal properties. Site descriptive modelling Forsmark - stage 2.2
International Nuclear Information System (INIS)
Back, Paer-Erik; Wrafter, John; Sundberg, Jan; Rosen, L ars
2007-09-01
The lithological data acquired from boreholes and mapping of the rock surface need to be reclassified into thermal rock classes, TRCs. The main reason is to simplify the simulations. The lithological data are used to construct models of the transition between different TRCs, thus describing the spatial statistical structure of each TRC. The result is a set of transition probability models that are used in the simulation of TRCs. The intermediate result of this first stochastic simulation is a number of realisations of the geology, each one equally probable. Based on the thermal data, a spatial statistical thermal model is constructed for each TRC. It consists of a statistical distribution and a variogram for each TRC. These are used in the stochastic simulation of thermal conductivity and the result is a number of equally probable realisations of thermal conductivity for the domain. In the next step, the realisations of TRCs (lithology) and thermal conductivity are merged, i.e. each realisation of geology is filled with simulated thermal conductivity values. The result is a set of realisations of thermal conductivity that considers both the difference in thermal properties between different TRCs, and the variability within each TRC. If the result is desired in a scale different from the simulation scale, i.e. the canister scale, upscaling of the realisations can be performed. The result is a set of equally probable realisations of thermal properties. The presented methodology was applied to rock domain RFM029 and RFM045. The main results are sets of realisations of thermal properties that can be used for further processing, most importantly for statistical analysis and numerical temperature simulations for the design of repository layout (distances between deposition holes). The main conclusions of the thermal modelling are: The choice of scale has a profound influence on the distribution of thermal conductivity values. The variance decreases and the lower tail
Thermal properties. Site descriptive modelling Forsmark - stage 2.2
Energy Technology Data Exchange (ETDEWEB)
Back, Paer-Erik; Wrafter, John; Sundberg, Jan [Geo Innova AB (Sweden); Rosen, L ars [Sweco Viak AB (Sweden)
2007-09-15
The lithological data acquired from boreholes and mapping of the rock surface need to be reclassified into thermal rock classes, TRCs. The main reason is to simplify the simulations. The lithological data are used to construct models of the transition between different TRCs, thus describing the spatial statistical structure of each TRC. The result is a set of transition probability models that are used in the simulation of TRCs. The intermediate result of this first stochastic simulation is a number of realisations of the geology, each one equally probable. Based on the thermal data, a spatial statistical thermal model is constructed for each TRC. It consists of a statistical distribution and a variogram for each TRC. These are used in the stochastic simulation of thermal conductivity and the result is a number of equally probable realisations of thermal conductivity for the domain. In the next step, the realisations of TRCs (lithology) and thermal conductivity are merged, i.e. each realisation of geology is filled with simulated thermal conductivity values. The result is a set of realisations of thermal conductivity that considers both the difference in thermal properties between different TRCs, and the variability within each TRC. If the result is desired in a scale different from the simulation scale, i.e. the canister scale, upscaling of the realisations can be performed. The result is a set of equally probable realisations of thermal properties. The presented methodology was applied to rock domain RFM029 and RFM045. The main results are sets of realisations of thermal properties that can be used for further processing, most importantly for statistical analysis and numerical temperature simulations for the design of repository layout (distances between deposition holes). The main conclusions of the thermal modelling are: The choice of scale has a profound influence on the distribution of thermal conductivity values. The variance decreases and the lower tail
Mckim, Stephen A.
2016-01-01
This thesis describes the development and correlation of a thermal model that forms the foundation of a thermal capacitance spacecraft propellant load estimator. Specific details of creating the thermal model for the diaphragm propellant tank used on NASA's Magnetospheric Multiscale spacecraft using ANSYS and the correlation process implemented are presented. The thermal model was correlated to within plus or minus 3 degrees Celsius of the thermal vacuum test data, and was determined sufficient to make future propellant predictions on MMS. The model was also found to be relatively sensitive to uncertainties in applied heat flux and mass knowledge of the tank. More work is needed to improve temperature predictions in the upper hemisphere of the propellant tank where predictions were found to be 2 to 2.5 C lower than the test data. A road map for applying the model to predict propellant loads on the actual MMS spacecraft toward its end of life in 2017-2018 is also presented.
Adaptive-network models of collective dynamics
Zschaler, G.
2012-09-01
Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this work, which is essentially my PhD thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system's collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge
Linear approximation model network and its formation via ...
Indian Academy of Sciences (India)
To overcome the deficiency of `local model network' (LMN) techniques, an alternative `linear approximation model' (LAM) network approach is proposed. Such a network models a nonlinear or practical system with multiple linear models fitted along operating trajectories, where individual models are simply networked ...
Modelling the structure of complex networks
DEFF Research Database (Denmark)
Herlau, Tue
networks has been independently studied as mathematical objects in their own right. As such, there has been both an increased demand for statistical methods for complex networks as well as a quickly growing mathematical literature on the subject. In this dissertation we explore aspects of modelling complex....... The next chapters will treat some of the various symmetries, representer theorems and probabilistic structures often deployed in the modelling complex networks, the construction of sampling methods and various network models. The introductory chapters will serve to provide context for the included written...
Directory of Open Access Journals (Sweden)
Jing Li
2017-01-01
Full Text Available The goal of this study is to improve thermal comfort and indoor air quality with the adaptive network-based fuzzy inference system (ANFIS model and improved particle swarm optimization (PSO algorithm. A method to optimize air conditioning parameters and installation distance is proposed. The methodology is demonstrated through a prototype case, which corresponds to a typical laboratory in colleges and universities. A laboratory model is established, and simulated flow field information is obtained with the CFD software. Subsequently, the ANFIS model is employed instead of the CFD model to predict indoor flow parameters, and the CFD database is utilized to train ANN input-output “metamodels” for the subsequent optimization. With the improved PSO algorithm and the stratified sequence method, the objective functions are optimized. The functions comprise PMV, PPD, and mean age of air. The optimal installation distance is determined with the hemisphere model. Results show that most of the staff obtain a satisfactory degree of thermal comfort and that the proposed method can significantly reduce the cost of building an experimental device. The proposed methodology can be used to determine appropriate air supply parameters and air conditioner installation position for a pleasant and healthy indoor environment.
Berrios, William M.
1992-01-01
The Long Duration Exposure Facility (LDEF) postflight thermal model predicted temperatures were matched to flight temperature data recorded by the Thermal Measurement System (THERM), LDEF experiment P0003. Flight temperatures, recorded at intervals of approximately 112 minutes for the first 390 days of LDEF's 2105 day mission were compared with predictions using the thermal mathematical model (TMM). This model was unverified prior to flight. The postflight analysis has reduced the thermal model uncertainty at the temperature sensor locations from +/- 40 F to +/- 18 F. The improved temperature predictions will be used by the LDEF's principal investigators to calculate improved flight temperatures experienced by 57 experiments located on 86 trays of the facility.
Spatial Epidemic Modelling in Social Networks
Simoes, Joana Margarida
2005-06-01
The spread of infectious diseases is highly influenced by the structure of the underlying social network. The target of this study is not the network of acquaintances, but the social mobility network: the daily movement of people between locations, in regions. It was already shown that this kind of network exhibits small world characteristics. The model developed is agent based (ABM) and comprehends a movement model and a infection model. In the movement model, some assumptions are made about its structure and the daily movement is decomposed into four types: neighborhood, intra region, inter region and random. The model is Geographical Information Systems (GIS) based, and uses real data to define its geometry. Because it is a vector model, some optimization techniques were used to increase its efficiency.
A turbulent transport network model in MULTIFLUX coupled with TOUGH2
International Nuclear Information System (INIS)
Danko, G.; Bahrami, D.; Birkholzer, J.T.
2011-01-01
A new numerical method is described for the fully iterated, conjugate solution of two discrete submodels, involving (a) a transport network model for heat, moisture, and airflows in a high-permeability, air-filled cavity; and (b) a variably saturated fractured porous medium. The transport network submodel is an integrated-parameter, computational fluid dynamics solver, describing the thermal-hydrologic transport processes in the flow channel system of the cavity with laminar or turbulent flow and convective heat and mass transport, using MULTIFLUX. The porous medium submodel, using TOUGH2, is a solver for the heat and mass transport in the fractured rock mass. The new model solution extends the application fields of TOUGH2 by integrating it with turbulent flow and transport in a discrete flow network system. We present demonstrational results for a nuclear waste repository application at Yucca Mountain with the most realistic model assumptions and input parameters including the geometrical layout of the nuclear spent fuel and waste with variable heat load for the individual containers. The MULTIFLUX and TOUGH2 model elements are fully iterated, applying a programmed reprocessing of the Numerical Transport Code Functionalization model-element in an automated Outside Balance Iteration loop. The natural, convective airflow field and the heat and mass transport in a representative emplacement drift during postclosure are explicitly solved in the new model. The results demonstrate that the direction and magnitude of the air circulation patterns and all transport modes are strongly affected by the heat and moisture transport processes in the surrounding rock, justifying the need for a coupled, fully iterated model solution such as the one presented in the paper.
Modeling of fluctuating reaction networks
International Nuclear Information System (INIS)
Lipshtat, A.; Biham, O.
2004-01-01
Full Text:Various dynamical systems are organized as reaction networks, where the population size of one component affects the populations of all its neighbors. Such networks can be found in interstellar surface chemistry, cell biology, thin film growth and other systems. I cases where the populations of reactive species are large, the network can be modeled by rate equations which provide all reaction rates within mean field approximation. However, in small systems that are partitioned into sub-micron size, these populations strongly fluctuate. Under these conditions rate equations fail and the master equation is needed for modeling these reactions. However, the number of equations in the master equation grows exponentially with the number of reactive species, severely limiting its feasibility for complex networks. Here we present a method which dramatically reduces the number of equations, thus enabling the incorporation of the master equation in complex reaction networks. The method is examplified in the context of reaction network on dust grains. Its applicability for genetic networks will be discussed. 1. Efficient simulations of gas-grain chemistry in interstellar clouds. Azi Lipshtat and Ofer Biham, Phys. Rev. Lett. 93 (2004), 170601. 2. Modeling of negative autoregulated genetic networks in single cells. Azi Lipshtat, Hagai B. Perets, Nathalie Q. Balaban and Ofer Biham, Gene: evolutionary genomics (2004), In press
Thermal-Aware Multiconstrained Intrabody QoS Routing for Wireless Body Area Networks
Muhammad Mostafa Monowar; Mohammad Mehedi Hassan; Fuad Bajaber; Md. Abdul Hamid; Atif Alamri
2014-01-01
Wireless body area networks (WBANs) can be formed including implanted biosensors for health monitoring and diagnostic purposes. However, implanted biosensors could cause thermal damages on human tissue as it exhibits temperature rise due to wireless communication and processing tasks inside the human body. Again, Quality of Service (QoS) provisioning with multiconstraints (delay and reliability) is a striking requirement for diverse application types in WBANs to meet their objectives. This pa...
Deterministic ripple-spreading model for complex networks.
Hu, Xiao-Bing; Wang, Ming; Leeson, Mark S; Hines, Evor L; Di Paolo, Ezequiel
2011-04-01
This paper proposes a deterministic complex network model, which is inspired by the natural ripple-spreading phenomenon. The motivations and main advantages of the model are the following: (i) The establishment of many real-world networks is a dynamic process, where it is often observed that the influence of a few local events spreads out through nodes, and then largely determines the final network topology. Obviously, this dynamic process involves many spatial and temporal factors. By simulating the natural ripple-spreading process, this paper reports a very natural way to set up a spatial and temporal model for such complex networks. (ii) Existing relevant network models are all stochastic models, i.e., with a given input, they cannot output a unique topology. Differently, the proposed ripple-spreading model can uniquely determine the final network topology, and at the same time, the stochastic feature of complex networks is captured by randomly initializing ripple-spreading related parameters. (iii) The proposed model can use an easily manageable number of ripple-spreading related parameters to precisely describe a network topology, which is more memory efficient when compared with traditional adjacency matrix or similar memory-expensive data structures. (iv) The ripple-spreading model has a very good potential for both extensions and applications.
Network model of security system
Directory of Open Access Journals (Sweden)
Adamczyk Piotr
2016-01-01
Full Text Available The article presents the concept of building a network security model and its application in the process of risk analysis. It indicates the possibility of a new definition of the role of the network models in the safety analysis. Special attention was paid to the development of the use of an algorithm describing the process of identifying the assets, vulnerability and threats in a given context. The aim of the article is to present how this algorithm reduced the complexity of the problem by eliminating from the base model these components that have no links with others component and as a result and it was possible to build a real network model corresponding to reality.
Neural network modeling of emotion
Levine, Daniel S.
2007-03-01
This article reviews the history and development of computational neural network modeling of cognitive and behavioral processes that involve emotion. The exposition starts with models of classical conditioning dating from the early 1970s. Then it proceeds toward models of interactions between emotion and attention. Then models of emotional influences on decision making are reviewed, including some speculative (not and not yet simulated) models of the evolution of decision rules. Through the late 1980s, the neural networks developed to model emotional processes were mainly embodiments of significant functional principles motivated by psychological data. In the last two decades, network models of these processes have become much more detailed in their incorporation of known physiological properties of specific brain regions, while preserving many of the psychological principles from the earlier models. Most network models of emotional processes so far have dealt with positive and negative emotion in general, rather than specific emotions such as fear, joy, sadness, and anger. But a later section of this article reviews a few models relevant to specific emotions: one family of models of auditory fear conditioning in rats, and one model of induced pleasure enhancing creativity in humans. Then models of emotional disorders are reviewed. The article concludes with philosophical statements about the essential contributions of emotion to intelligent behavior and the importance of quantitative theories and models to the interdisciplinary enterprise of understanding the interactions of emotion, cognition, and behavior.
Numerical modeling of aquifer thermal energy storage system
Energy Technology Data Exchange (ETDEWEB)
Kim, Jongchan [Korea Institute of Geoscience and Mineral Resources, Geothermal Resources Department, 92 Gwahang-no, Yuseong-gu, Daejeon 305-350 (Korea, Republic of); Kongju National University, Department of Geoenvironmental Sciences, 182 Singwan-dong, Gongju-si, Chungnam 314-701 (Korea, Republic of); Lee, Youngmin [Korea Institute of Geoscience and Mineral Resources, Geothermal Resources Department, 92 Gwahang-no, Yuseong-gu, Daejeon 305-350 (Korea, Republic of); Yoon, Woon Sang; Jeon, Jae Soo [nexGeo Inc., 134-1 Garak 2-dong, Songpa-gu, Seoul 138-807 (Korea, Republic of); Koo, Min-Ho; Keehm, Youngseuk [Kongju National University, Department of Geoenvironmental Sciences, 182 Singwan-dong, Gongju-si, Chungnam 314-701 (Korea, Republic of)
2010-12-15
The performance of the ATES (aquifer thermal energy storage) system primarily depends on the thermal interference between warm and cold thermal energy stored in an aquifer. Additionally the thermal interference is mainly affected by the borehole distance, the hydraulic conductivity, and the pumping/injection rate. Thermo-hydraulic modeling was performed to identify the thermal interference by three parameters and to estimate the system performance change by the thermal interference. Modeling results indicate that the thermal interference grows as the borehole distance decreases, as the hydraulic conductivity increases, and as the pumping/injection rate increases. The system performance analysis indicates that if {eta} (the ratio of the length of the thermal front to the distance between two boreholes) is lower than unity, the system performance is not significantly affected, but if {eta} is equal to unity, the system performance falls up to {proportional_to}22%. Long term modeling for a factory in Anseong was conducted to test the applicability of the ATES system. When the pumping/injection rate is 100 m{sup 3}/day, system performances during the summer and winter after 3 years of operation are estimated to be {proportional_to}125 kW and {proportional_to}110 kW, respectively. Therefore, 100 m{sup 3}/day of the pumping/injection rate satisfies the energy requirements ({proportional_to}70 kW) for the factory. (author)
Final report of the 'Nordic thermal-hydraulic and safety network (NOTNET)' - Project
International Nuclear Information System (INIS)
Tuunanen, J.; Tuomainen, M.
2005-04-01
A Nordic network for thermal-hydraulics and nuclear safety research was started. The idea of the network is to combine the resources of different research teams in order to carry out more ambitious and extensive research programs than would be possible for the individual teams. From the very beginning, the end users of the research results have been integrated to the network. Aim of the network is to benefit the partners involved in nuclear energy in the Nordic Countries (power companies, reactor vendors, safety regulators, research units). First task within the project was to describe the resources (personnel, know-how, simulation tools, test facilities) of the various teams. Next step was to discuss with the end users about their research needs. Based on these steps, few most important research topics with defined goals were selected, and coarse road maps were prepared for reaching the targets. These road maps will be used as a starting point for planning the actual research projects in the future. The organisation and work plan for the network were established. National coordinators were appointed, as well as contact persons in each participating organisation, whether research unit or end user. This organisation scheme is valid for the short-term operation of NOTNET when only Nordic organisations take part in the work. Later on, it is possible to enlarge the network e.g. within EC framework programme. The network can now start preparing project proposals and searching funding for the first common research projects. (au)
Development and evaluation of thermal model reduction algorithms for spacecraft
Deiml, Michael; Suderland, Martin; Reiss, Philipp; Czupalla, Markus
2015-05-01
This paper is concerned with the topic of the reduction of thermal models of spacecraft. The work presented here has been conducted in cooperation with the company OHB AG, formerly Kayser-Threde GmbH, and the Institute of Astronautics at Technische Universität München with the goal to shorten and automatize the time-consuming and manual process of thermal model reduction. The reduction of thermal models can be divided into the simplification of the geometry model for calculation of external heat flows and radiative couplings and into the reduction of the underlying mathematical model. For simplification a method has been developed which approximates the reduced geometry model with the help of an optimization algorithm. Different linear and nonlinear model reduction techniques have been evaluated for their applicability in reduction of the mathematical model. Thereby the compatibility with the thermal analysis tool ESATAN-TMS is of major concern, which restricts the useful application of these methods. Additional model reduction methods have been developed, which account to these constraints. The Matrix Reduction method allows the approximation of the differential equation to reference values exactly expect for numerical errors. The summation method enables a useful, applicable reduction of thermal models that can be used in industry. In this work a framework for model reduction of thermal models has been created, which can be used together with a newly developed graphical user interface for the reduction of thermal models in industry.
Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance
Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.
2014-01-01
This paper presents recent thermal model results of the Advanced Stirling Radioisotope Generator (ASRG). The three-dimensional (3D) ASRG thermal power model was built using the Thermal Desktop(trademark) thermal analyzer. The model was correlated with ASRG engineering unit test data and ASRG flight unit predictions from Lockheed Martin's (LM's) I-deas(trademark) TMG thermal model. The auxiliary cooling system (ACS) of the ASRG is also included in the ASRG thermal model. The ACS is designed to remove waste heat from the ASRG so that it can be used to heat spacecraft components. The performance of the ACS is reported under nominal conditions and during a Venus flyby scenario. The results for the nominal case are validated with data from Lockheed Martin. Transient thermal analysis results of ASRG for a Venus flyby with a representative trajectory are also presented. In addition, model results of an ASRG mounted on a Cassini-like spacecraft with a sunshade are presented to show a way to mitigate the high temperatures of a Venus flyby. It was predicted that the sunshade can lower the temperature of the ASRG alternator by 20 C for the representative Venus flyby trajectory. The 3D model also was modified to predict generator performance after a single Advanced Stirling Convertor failure. The geometry of the Microtherm HT insulation block on the outboard side was modified to match deformation and shrinkage observed during testing of a prototypic ASRG test fixture by LM. Test conditions and test data were used to correlate the model by adjusting the thermal conductivity of the deformed insulation to match the post-heat-dump steady state temperatures. Results for these conditions showed that the performance of the still-functioning inboard ACS was unaffected.
An acoustical model based monitoring network
Wessels, P.W.; Basten, T.G.H.; Eerden, F.J.M. van der
2010-01-01
In this paper the approach for an acoustical model based monitoring network is demonstrated. This network is capable of reconstructing a noise map, based on the combination of measured sound levels and an acoustic model of the area. By pre-calculating the sound attenuation within the network the
How to model wireless mesh networks topology
International Nuclear Information System (INIS)
Sanni, M L; Hashim, A A; Anwar, F; Ali, S; Ahmed, G S M
2013-01-01
The specification of network connectivity model or topology is the beginning of design and analysis in Computer Network researches. Wireless Mesh Networks is an autonomic network that is dynamically self-organised, self-configured while the mesh nodes establish automatic connectivity with the adjacent nodes in the relay network of wireless backbone routers. Researches in Wireless Mesh Networks range from node deployment to internetworking issues with sensor, Internet and cellular networks. These researches require modelling of relationships and interactions among nodes including technical characteristics of the links while satisfying the architectural requirements of the physical network. However, the existing topology generators model geographic topologies which constitute different architectures, thus may not be suitable in Wireless Mesh Networks scenarios. The existing methods of topology generation are explored, analysed and parameters for their characterisation are identified. Furthermore, an algorithm for the design of Wireless Mesh Networks topology based on square grid model is proposed in this paper. The performance of the topology generated is also evaluated. This research is particularly important in the generation of a close-to-real topology for ensuring relevance of design to the intended network and validity of results obtained in Wireless Mesh Networks researches
Numerical Modeling of Water Thermal Plumes Emitted by Thermal Power Plants
Directory of Open Access Journals (Sweden)
Azucena Durán-Colmenares
2016-10-01
Full Text Available This work focuses on the study of thermal dispersion of plumes emitted by power plants into the sea. Wastewater discharge from power stations causes impacts that require investigation or monitoring. A study to characterize the physical effects of thermal plumes into the sea is carried out here by numerical modeling and field measurements. The case study is the thermal discharges of the Presidente Adolfo López Mateos Power Plant, located in Veracruz, on the coast of the Gulf of Mexico. This plant is managed by the Federal Electricity Commission of Mexico. The physical effects of such plumes are related to the increase of seawater temperature caused by the hot water discharge of the plant. We focus on the implementation, calibration, and validation of the Delft3D-FLOW model, which solves the shallow-water equations. The numerical simulations consider a critical scenario where meteorological and oceanographic parameters are taken into account to reproduce the proper physical conditions of the environment. The results show a local physical effect of the thermal plumes within the study zone, given the predominant strong winds conditions of the scenario under study.
Thermal-Hydraulic Experiments and Modelling for Advanced Nuclear Reactor Systems
International Nuclear Information System (INIS)
Song, C. H.; Baek, W. P.; Chung, M. K.
2007-06-01
The objectives of the project are to study thermal hydraulic characteristics of advanced nuclear reactor system for evaluating key thermal-hydraulic phenomena relevant to new safety concepts. To meet the research goal, several thermal hydraulic experiments were performed and related thermal hydraulic models were developed with the experimental data which were produced through the thermal hydraulic experiments. The Followings are main research topics: - Multi-dimensional Phenomena in a Reactor Vessel Downcomer - Condensation-induced Thermal Mixing in a Pool - Development of Thermal-Hydraulic Models for Two-Phase Flow - Construction of T-H Data Base
Modeling the interdependent network based on two-mode networks
An, Feng; Gao, Xiangyun; Guan, Jianhe; Huang, Shupei; Liu, Qian
2017-10-01
Among heterogeneous networks, there exist obviously and closely interdependent linkages. Unlike existing research primarily focus on the theoretical research of physical interdependent network model. We propose a two-layer interdependent network model based on two-mode networks to explore the interdependent features in the reality. Specifically, we construct a two-layer interdependent loan network and develop several dependent features indices. The model is verified to enable us to capture the loan dependent features of listed companies based on loan behaviors and shared shareholders. Taking Chinese debit and credit market as case study, the main conclusions are: (1) only few listed companies shoulder the main capital transmission (20% listed companies occupy almost 70% dependent degree). (2) The control of these key listed companies will be more effective of avoiding the spreading of financial risks. (3) Identifying the companies with high betweenness centrality and controlling them could be helpful to monitor the financial risk spreading. (4) The capital transmission channel among Chinese financial listed companies and Chinese non-financial listed companies are relatively strong. However, under greater pressure of demand of capital transmission (70% edges failed), the transmission channel, which constructed by debit and credit behavior, will eventually collapse.
Radial lip seals, thermal aspects
Stakenborg, M.J.L.; van Ostaijen, R.A.J.; Dowson, D.
1989-01-01
In this paper the influence of temperature on tne seal-snarc contact is studied, using coupled temperature-stress FEH analysis. A thermal network model is used to calculate the seal-shaft contact temperature for steady-state and transient conditions. Contact temperatures were measured under the seal
Entropy Characterization of Random Network Models
Directory of Open Access Journals (Sweden)
Pedro J. Zufiria
2017-06-01
Full Text Available This paper elaborates on the Random Network Model (RNM as a mathematical framework for modelling and analyzing the generation of complex networks. Such framework allows the analysis of the relationship between several network characterizing features (link density, clustering coefficient, degree distribution, connectivity, etc. and entropy-based complexity measures, providing new insight on the generation and characterization of random networks. Some theoretical and computational results illustrate the utility of the proposed framework.
The model of social crypto-network
Directory of Open Access Journals (Sweden)
Марк Миколайович Орел
2015-06-01
Full Text Available The article presents the theoretical model of social network with the enhanced mechanism of privacy policy. It covers the problems arising in the process of implementing the mentioned type of network. There are presented the methods of solving problems arising in the process of building the social network with privacy policy. It was built a theoretical model of social networks with enhanced information protection methods based on information and communication blocks
Ichinohe, Y.; Yamada, S.; Miyazaki, N.; Saito, S.
2018-04-01
We present data preprocessing based on an artificial neural network to estimate the parameters of the X-ray emission spectra of a single-temperature thermal plasma. The method finds appropriate parameters close to the global optimum. The neural network is designed to learn the parameters of the thermal plasma (temperature, abundance, normalization and redshift) of the input spectra. After training using 9000 simulated X-ray spectra, the network has grown to predict all the unknown parameters with uncertainties of about a few per cent. The performance dependence on the network structure has been studied. We applied the neural network to an actual high-resolution spectrum obtained with Hitomi. The predicted plasma parameters agree with the known best-fitting parameters of the Perseus cluster within uncertainties of ≲10 per cent. The result shows that neural networks trained by simulated data might possibly be used to extract a feature built in the data. This would reduce human-intensive preprocessing costs before detailed spectral analysis, and would help us make the best use of the large quantities of spectral data that will be available in the coming decades.
Towards reproducible descriptions of neuronal network models.
Directory of Open Access Journals (Sweden)
Eilen Nordlie
2009-08-01
Full Text Available Progress in science depends on the effective exchange of ideas among scientists. New ideas can be assessed and criticized in a meaningful manner only if they are formulated precisely. This applies to simulation studies as well as to experiments and theories. But after more than 50 years of neuronal network simulations, we still lack a clear and common understanding of the role of computational models in neuroscience as well as established practices for describing network models in publications. This hinders the critical evaluation of network models as well as their re-use. We analyze here 14 research papers proposing neuronal network models of different complexity and find widely varying approaches to model descriptions, with regard to both the means of description and the ordering and placement of material. We further observe great variation in the graphical representation of networks and the notation used in equations. Based on our observations, we propose a good model description practice, composed of guidelines for the organization of publications, a checklist for model descriptions, templates for tables presenting model structure, and guidelines for diagrams of networks. The main purpose of this good practice is to trigger a debate about the communication of neuronal network models in a manner comprehensible to humans, as opposed to machine-readable model description languages. We believe that the good model description practice proposed here, together with a number of other recent initiatives on data-, model-, and software-sharing, may lead to a deeper and more fruitful exchange of ideas among computational neuroscientists in years to come. We further hope that work on standardized ways of describing--and thinking about--complex neuronal networks will lead the scientific community to a clearer understanding of high-level concepts in network dynamics, and will thus lead to deeper insights into the function of the brain.
Designing Network-based Business Model Ontology
DEFF Research Database (Denmark)
Hashemi Nekoo, Ali Reza; Ashourizadeh, Shayegheh; Zarei, Behrouz
2015-01-01
Survival on dynamic environment is not achieved without a map. Scanning and monitoring of the market show business models as a fruitful tool. But scholars believe that old-fashioned business models are dead; as they are not included the effect of internet and network in themselves. This paper...... is going to propose e-business model ontology from the network point of view and its application in real world. The suggested ontology for network-based businesses is composed of individuals` characteristics and what kind of resources they own. also, their connections and pre-conceptions of connections...... such as shared-mental model and trust. However, it mostly covers previous business model elements. To confirm the applicability of this ontology, it has been implemented in business angel network and showed how it works....
An Improved Car-Following Model in Vehicle Networking Based on Network Control
Directory of Open Access Journals (Sweden)
D. Y. Kong
2014-01-01
Full Text Available Vehicle networking is a system to realize information interoperability between vehicles and people, vehicles and roads, vehicles and vehicles, and cars and transport facilities, through the network information exchange, in order to achieve the effective monitoring of the vehicle and traffic flow. Realizing information interoperability between vehicles and vehicles, which can affect the traffic flow, is an important application of network control system (NCS. In this paper, a car-following model using vehicle networking theory is established, based on network control principle. The car-following model, which is an improvement of the traditional traffic model, describes the traffic in vehicle networking condition. The impact that vehicle networking has on the traffic flow is quantitatively assessed in a particular scene of one-way, no lane changing highway. The examples show that the capacity of the road is effectively enhanced by using vehicle networking.
Multiplicative Attribute Graph Model of Real-World Networks
Energy Technology Data Exchange (ETDEWEB)
Kim, Myunghwan [Stanford Univ., CA (United States); Leskovec, Jure [Stanford Univ., CA (United States)
2010-10-20
Large scale real-world network data, such as social networks, Internet andWeb graphs, is ubiquitous in a variety of scientific domains. The study of such social and information networks commonly finds patterns and explain their emergence through tractable models. In most networks, especially in social networks, nodes also have a rich set of attributes (e.g., age, gender) associatedwith them. However, most of the existing network models focus only on modeling the network structure while ignoring the features of nodes in the network. Here we present a class of network models that we refer to as the Multiplicative Attribute Graphs (MAG), which naturally captures the interactions between the network structure and node attributes. We consider a model where each node has a vector of categorical features associated with it. The probability of an edge between a pair of nodes then depends on the product of individual attributeattribute similarities. The model yields itself to mathematical analysis as well as fit to real data. We derive thresholds for the connectivity, the emergence of the giant connected component, and show that the model gives rise to graphs with a constant diameter. Moreover, we analyze the degree distribution to show that the model can produce networks with either lognormal or power-law degree distribution depending on certain conditions.
Developing Personal Network Business Models
DEFF Research Database (Denmark)
Saugstrup, Dan; Henten, Anders
2006-01-01
The aim of the paper is to examine the issue of business modeling in relation to personal networks, PNs. The paper builds on research performed on business models in the EU 1ST MAGNET1 project (My personal Adaptive Global NET). The paper presents the Personal Network concept and briefly reports...
Analytical modeling for thermal errors of motorized spindle unit
Liu, Teng; Gao, Weiguo; Zhang, Dawei; Zhang, Yifan; Chang, Wenfen; Liang, Cunman; Tian, Yanling
2017-01-01
Modeling method investigation about spindle thermal errors is significant for spindle thermal optimization in design phase. To accurately analyze the thermal errors of motorized spindle unit, this paper assumes approximately that 1) spindle linear thermal error on axial direction is ascribed to shaft thermal elongation for its heat transfer from bearings, and 2) spindle linear thermal errors on radial directions and angular thermal errors are attributed to thermal variations of bearing relati...
A novel Direct Small World network model
Directory of Open Access Journals (Sweden)
LIN Tao
2016-10-01
Full Text Available There is a certain degree of redundancy and low efficiency of existing computer networks.This paper presents a novel Direct Small World network model in order to optimize networks.In this model,several nodes construct a regular network.Then,randomly choose and replot some nodes to generate Direct Small World network iteratively.There is no change in average distance and clustering coefficient.However,the network performance,such as hops,is improved.The experiments prove that compared to traditional small world network,the degree,average of degree centrality and average of closeness centrality are lower in Direct Small World network.This illustrates that the nodes in Direct Small World networks are closer than Watts-Strogatz small world network model.The Direct Small World can be used not only in the communication of the community information,but also in the research of epidemics.
Optimization of thermal neutron shield concrete mixture using artificial neural network
Energy Technology Data Exchange (ETDEWEB)
Yadollahi, A. [Engineering Department, Shahid Beheshti University, G.C., P.O. Box: 1983963113, Tehran (Iran, Islamic Republic of); Nazemi, E., E-mail: nazemi.ehsan@yahoo.com [Young Researchers and Elite Club, Kermanshah Branch, Islamic Azad University, Kermanshah (Iran, Islamic Republic of); Zolfaghari, A. [Engineering Department, Shahid Beheshti University, G.C., P.O. Box: 1983963113, Tehran (Iran, Islamic Republic of); Ajorloo, A.M. [Water and Environmental Engineering Department, Shahid Beheshti University, P.O. Box: 167651719, Tehran (Iran, Islamic Republic of)
2016-08-15
Highlights: • Colemanite was used in fabricating of thermal neutron shield concrete. • The Taguchi method was implemented to obtain the data set required for training the ANN. • Trained ANN predicted quality characteristics of thermal neutron shield. - Abstract: Colemanite is the most convenient boron mineral which has been widely used in construction of radiation shielding concrete in order to improve the capture of thermal neutrons. But utilization of Colemanite in radiation shielding concrete has a deleterious effect on both physical and mechanical properties. In the present work, Taguchi method and artificial neural network (ANN) were employed to find an optimal mixture of Colemanite based concrete in order to improve the boron content of concrete and increase thermal neutron absorption without violating the standards for physical and mechanical properties. Using Taguchi method for experimental design, 27 concrete samples with different mixtures were fabricated and tested. Water/cement ratio, cement quantity, volume fraction of Colemanite aggregate and silica fume quantity were selected as control factors, and compressive strength, ultrasonic pulse velocity and thermal neutron transmission ratio were considered as the quality responses. Obtained data from 27 experiments were used to train 3 ANNs. Four control factors were utilized as the inputs of 3 ANNs and 3 quality responses were used as the outputs, separately (each ANN for one quality response). After training the ANNs, 1024 different mixtures with different quality responses were predicted. At the final, optimum mixture was obtained among the predicted different mixtures. Results demonstrated that the optimal mixture of thermal neutron shielding concrete has a water–cement ratio of 0.38, cement content of 400 kg/m{sup 3}, a volume fraction Colemanite aggregate of 50% and silica fume–cement ratio of 0.15.
Optimization of thermal neutron shield concrete mixture using artificial neural network
International Nuclear Information System (INIS)
Yadollahi, A.; Nazemi, E.; Zolfaghari, A.; Ajorloo, A.M.
2016-01-01
Highlights: • Colemanite was used in fabricating of thermal neutron shield concrete. • The Taguchi method was implemented to obtain the data set required for training the ANN. • Trained ANN predicted quality characteristics of thermal neutron shield. - Abstract: Colemanite is the most convenient boron mineral which has been widely used in construction of radiation shielding concrete in order to improve the capture of thermal neutrons. But utilization of Colemanite in radiation shielding concrete has a deleterious effect on both physical and mechanical properties. In the present work, Taguchi method and artificial neural network (ANN) were employed to find an optimal mixture of Colemanite based concrete in order to improve the boron content of concrete and increase thermal neutron absorption without violating the standards for physical and mechanical properties. Using Taguchi method for experimental design, 27 concrete samples with different mixtures were fabricated and tested. Water/cement ratio, cement quantity, volume fraction of Colemanite aggregate and silica fume quantity were selected as control factors, and compressive strength, ultrasonic pulse velocity and thermal neutron transmission ratio were considered as the quality responses. Obtained data from 27 experiments were used to train 3 ANNs. Four control factors were utilized as the inputs of 3 ANNs and 3 quality responses were used as the outputs, separately (each ANN for one quality response). After training the ANNs, 1024 different mixtures with different quality responses were predicted. At the final, optimum mixture was obtained among the predicted different mixtures. Results demonstrated that the optimal mixture of thermal neutron shielding concrete has a water–cement ratio of 0.38, cement content of 400 kg/m 3 , a volume fraction Colemanite aggregate of 50% and silica fume–cement ratio of 0.15.
International Nuclear Information System (INIS)
Lo Cascio, Ermanno; Borelli, Davide; Devia, Francesco; Schenone, Corrado
2017-01-01
Highlights: • Multi-objective optimization model for retrofitted and integrated natural gas pressure regulation stations. • Comparison of different incentive mechanisms for recovered energy based on the characteristics of preheating process. • Control strategies comparison: performances achieved with optimal control vs. ones obtained by thermal load tracking. - Abstract: A multi-objective optimization model for urban integrated electrical, thermal and gas grids is presented. The main system consists of a retrofitted natural gas pressure regulation station where a turbo-expander allows to recover energy from the process. Here, the natural gas must be preheated in order to avoid methane hydrates. The preheating phase could be based on fossil fuels, renewable or on a thermal mix. Depending on the system configuration, the proposed optimization model enables a proper differentiation based on how the natural gas preheating process is expected to be accomplished. This differentiation is addressed by weighting the electricity produced by the turbo-expander and linking it to proper remuneration tariffs. The effectiveness of the model has been tested on an existing plant located in the city of Genoa. Here, the thermal energy is provided by means of two redundant gas-fired boilers and a cogeneration unit. Furthermore, the whole system is thermally integrated with a district heating network. Numerical simulation results, obtained with the commercial proprietary software Honeywell UniSim Design Suite, have been compared with the optimal solutions achieved. The effectiveness of the model, in terms of economic and environmental performances, is finally quantified. For specific conditions, the model allows achieving an operational costs reduction of about 17% with the respect to thermal-load-tracking control logic.
A computational model for thermal fluid design analysis of nuclear thermal rockets
International Nuclear Information System (INIS)
Given, J.A.; Anghaie, S.
1997-01-01
A computational model for simulation and design analysis of nuclear thermal propulsion systems has been developed. The model simulates a full-topping expander cycle engine system and the thermofluid dynamics of the core coolant flow, accounting for the real gas properties of the hydrogen propellant/coolant throughout the system. Core thermofluid studies reveal that near-wall heat transfer models currently available may not be applicable to conditions encountered within some nuclear rocket cores. Additionally, the possibility of a core thermal fluid instability at low mass fluxes and the effects of the core power distribution are investigated. Results indicate that for tubular core coolant channels, thermal fluid instability is not an issue within the possible range of operating conditions in these systems. Findings also show the advantages of having a nonflat centrally peaking axial core power profile from a fluid dynamic standpoint. The effects of rocket operating conditions on system performance are also investigated. Results show that high temperature and low pressure operation is limited by core structural considerations, while low temperature and high pressure operation is limited by system performance constraints. The utility of these programs for finding these operational limits, optimum operating conditions, and thermal fluid effects is demonstrated
Non-consensus Opinion Models on Complex Networks
Li, Qian; Braunstein, Lidia A.; Wang, Huijuan; Shao, Jia; Stanley, H. Eugene; Havlin, Shlomo
2013-04-01
Social dynamic opinion models have been widely studied to understand how interactions among individuals cause opinions to evolve. Most opinion models that utilize spin interaction models usually produce a consensus steady state in which only one opinion exists. Because in reality different opinions usually coexist, we focus on non-consensus opinion models in which above a certain threshold two opinions coexist in a stable relationship. We revisit and extend the non-consensus opinion (NCO) model introduced by Shao et al. (Phys. Rev. Lett. 103:01870, 2009). The NCO model in random networks displays a second order phase transition that belongs to regular mean field percolation and is characterized by the appearance (above a certain threshold) of a large spanning cluster of the minority opinion. We generalize the NCO model by adding a weight factor W to each individual's original opinion when determining their future opinion (NCO W model). We find that as W increases the minority opinion holders tend to form stable clusters with a smaller initial minority fraction than in the NCO model. We also revisit another non-consensus opinion model based on the NCO model, the inflexible contrarian opinion (ICO) model (Li et al. in Phys. Rev. E 84:066101, 2011), which introduces inflexible contrarians to model the competition between two opinions in a steady state. Inflexible contrarians are individuals that never change their original opinion but may influence the opinions of others. To place the inflexible contrarians in the ICO model we use two different strategies, random placement and one in which high-degree nodes are targeted. The inflexible contrarians effectively decrease the size of the largest rival-opinion cluster in both strategies, but the effect is more pronounced under the targeted method. All of the above models have previously been explored in terms of a single network, but human communities are usually interconnected, not isolated. Because opinions propagate not
Modeling of thermalization phenomena in coaxial plasma accelerators
Subramaniam, Vivek; Panneerchelvam, Premkumar; Raja, Laxminarayan L.
2018-05-01
Coaxial plasma accelerators are electromagnetic acceleration devices that employ a self-induced Lorentz force to produce collimated plasma jets with velocities ~50 km s‑1. The accelerator operation is characterized by the formation of an ionization/thermalization zone near gas inlet of the device that continually processes the incoming neutral gas into a highly ionized thermal plasma. In this paper, we present a 1D non-equilibrium plasma model to resolve the plasma formation and the electron-heavy species thermalization phenomena that take place in the thermalization zone. The non-equilibrium model is based on a self-consistent multi-species continuum description of the plasma with finite-rate chemistry. The thermalization zone is modelled by tracking a 1D gas-bit as it convects down the device with an initial gas pressure of 1 atm. The thermalization process occurs in two stages. The first is a plasma production stage, associated with a rapid increase in the charged species number densities facilitated by cathode surface electron emission and volumetric production processes. The production stage results in the formation of a two-temperature plasma with electron energies of ~2.5 eV in a low temperature background gas of ~300 K. The second, a temperature equilibration stage, is characterized by the energy transfer between the electrons and heavy species. The characteristic length scale for thermalization is found to be comparable to axial length of the accelerator thus putting into question the equilibrium magnetohydrodynamics assumption used in modeling coaxial accelerators.
A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network
Zhang, C.; Qin, T. X.; Jiang, B.; Huang, C.
2018-02-01
Oil pipelines network is one of the most important facilities of energy transportation. But oil pipelines network accident may result in serious disasters. Some analysis models for these accidents have been established mainly based on three methods, including event-tree, accident simulation and Bayesian network. Among these methods, Bayesian network is suitable for probabilistic analysis. But not all the important influencing factors are considered and the deployment rule of the factors has not been established. This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network. Most of the important influencing factors, including the key environment condition and emergency response are considered in this model. Moreover, the paper also introduces a deployment rule for these factors. The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.
Network structure exploration via Bayesian nonparametric models
International Nuclear Information System (INIS)
Chen, Y; Wang, X L; Xiang, X; Tang, B Z; Bu, J Z
2015-01-01
Complex networks provide a powerful mathematical representation of complex systems in nature and society. To understand complex networks, it is crucial to explore their internal structures, also called structural regularities. The task of network structure exploration is to determine how many groups there are in a complex network and how to group the nodes of the network. Most existing structure exploration methods need to specify either a group number or a certain type of structure when they are applied to a network. In the real world, however, the group number and also the certain type of structure that a network has are usually unknown in advance. To explore structural regularities in complex networks automatically, without any prior knowledge of the group number or the certain type of structure, we extend a probabilistic mixture model that can handle networks with any type of structure but needs to specify a group number using Bayesian nonparametric theory. We also propose a novel Bayesian nonparametric model, called the Bayesian nonparametric mixture (BNPM) model. Experiments conducted on a large number of networks with different structures show that the BNPM model is able to explore structural regularities in networks automatically with a stable, state-of-the-art performance. (paper)
Forty years of Fanger's model of thermal comfort: comfort for all?
van Hoof, J
2008-06-01
The predicted mean vote (PMV) model of thermal comfort, created by Fanger in the late 1960s, is used worldwide to assess thermal comfort. Fanger based his model on college-aged students for use in invariant environmental conditions in air-conditioned buildings in moderate thermal climate zones. Environmental engineering practice calls for a predictive method that is applicable to all types of people in any kind of building in every climate zone. In this publication, existing support and criticism, as well as modifications to the PMV model are discussed in light of the requirements by environmental engineering practice in the 21st century in order to move from a predicted mean vote to comfort for all. Improved prediction of thermal comfort can be achieved through improving the validity of the PMV model, better specification of the model's input parameters, and accounting for outdoor thermal conditions and special groups. The application range of the PMV model can be enlarged, for instance, by using the model to assess the effects of the thermal environment on productivity and behavior, and interactions with other indoor environmental parameters, and the use of information and communication technologies. Even with such modifications to thermal comfort evaluation, thermal comfort for all can only be achieved when occupants have effective control over their own thermal environment. The paper treats the assessment of thermal comfort using the PMV model of Fanger, and deals with the strengths and limitations of this model. Readers are made familiar to some opportunities for use in the 21st-century information society.
Directory of Open Access Journals (Sweden)
Yanlei Li
2015-01-01
Full Text Available This paper proposes a new method for predicting spindle deformation based on temperature data. The method introduces the adaptive neurofuzzy inference system (ANFIS, which is a neurofuzzy modeling approach that integrates the kernel and geometrical transformations. By utilizing data transformation, the number of ANFIS rules can be effectively reduced and the predictive model structure can be simplified. To build the predictive model, we first map the original temperature data to a feature space with Gaussian kernels. We then process the mapped data with the geometrical transformation and make the data gather in the square region. Finally, the transformed data are used as input to train the ANFIS. A verification experiment is conducted to evaluate the performance of the proposed method. Six Pt100 thermal resistances are used to monitor the spindle temperature, and a laser displacement sensor is used to detect the spindle deformation. Experimental results show that the proposed method can precisely predict the spindle deformation and greatly improve the thermal performance of the spindle. Compared with back propagation (BP networks, the proposed method is more suitable for complex working conditions in practical applications.
Homophyly/Kinship Model: Naturally Evolving Networks
Li, Angsheng; Li, Jiankou; Pan, Yicheng; Yin, Xianchen; Yong, Xi
2015-10-01
It has been a challenge to understand the formation and roles of social groups or natural communities in the evolution of species, societies and real world networks. Here, we propose the hypothesis that homophyly/kinship is the intrinsic mechanism of natural communities, introduce the notion of the affinity exponent and propose the homophyly/kinship model of networks. We demonstrate that the networks of our model satisfy a number of topological, probabilistic and combinatorial properties and, in particular, that the robustness and stability of natural communities increase as the affinity exponent increases and that the reciprocity of the networks in our model decreases as the affinity exponent increases. We show that both homophyly/kinship and reciprocity are essential to the emergence of cooperation in evolutionary games and that the homophyly/kinship and reciprocity determined by the appropriate affinity exponent guarantee the emergence of cooperation in evolutionary games, verifying Darwin’s proposal that kinship and reciprocity are the means of individual fitness. We propose the new principle of structure entropy minimisation for detecting natural communities of networks and verify the functional module property and characteristic properties by a healthy tissue cell network, a citation network, some metabolic networks and a protein interaction network.
Modeling, robust and distributed model predictive control for freeway networks
Liu, S.
2016-01-01
In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of
International Nuclear Information System (INIS)
Sundberg, Jan
2003-04-01
Site investigations are in progress for the siting of a deep repository for spent nuclear fuel. As part of the planning work, strategies are developed for site descriptive modelling regarding different disciplines, amongst them the thermal conditions. The objective of the strategy for a thermal site descriptive model is to guide the practical implementation of evaluating site specific data during the site investigations. It is understood that further development may be needed. The model describes the thermal properties and other thermal parameters of intact rock, fractures and fracture zones, and of the rock mass. The methodology is based on estimation of thermal properties of intact rock and discontinuities, using both empirical and theoretical/numerical approaches, and estimation of thermal processes using mathematical modelling. The methodology will be used and evaluated for the thermal site descriptive modelling at the Aespoe Hard Rock Laboratory
Li, Hua; Wang, Xiaogui; Yan, Guoping; Lam, K. Y.; Cheng, Sixue; Zou, Tao; Zhuo, Renxi
2005-03-01
In this paper, a novel multiphysic mathematical model is developed for simulation of swelling equilibrium of ionized temperature sensitive hydrogels with the volume phase transition, and it is termed the multi-effect-coupling thermal-stimulus (MECtherm) model. This model consists of the steady-state Nernst-Planck equation, Poisson equation and swelling equilibrium governing equation based on the Flory's mean field theory, in which two types of polymer-solvent interaction parameters, as the functions of temperature and polymer-network volume fraction, are specified with or without consideration of the hydrogen bond interaction. In order to examine the MECtherm model consisting of nonlinear partial differential equations, a meshless Hermite-Cloud method is used for numerical solution of one-dimensional swelling equilibrium of thermal-stimulus responsive hydrogels immersed in a bathing solution. The computed results are in very good agreements with experimental data for the variation of volume swelling ratio with temperature. The influences of the salt concentration and initial fixed-charge density are discussed in detail on the variations of volume swelling ratio of hydrogels, mobile ion concentrations and electric potential of both interior hydrogels and exterior bathing solution.
An improved thermal model for the computer code NAIAD
International Nuclear Information System (INIS)
Rainbow, M.T.
1982-12-01
An improved thermal model, based on the concept of heat slabs, has been incorporated as an option into the thermal hydraulic computer code NAIAD. The heat slabs are one-dimensional thermal conduction models with temperature independent thermal properties which may be internal and/or external to the fluid. Thermal energy may be added to or removed from the fluid via heat slabs and passed across the external boundary of external heat slabs at a rate which is a linear function of the external surface temperatures. The code input for the new option has been restructured to simplify data preparation. A full description of current input requirements is presented
A new thermal conductivity model for nanofluids
Energy Technology Data Exchange (ETDEWEB)
Koo, Junemoo; Kleinstreuer, Clement [Department of Mechanical and Aerospace Engineering (United States)], E-mail: ck@eos.ncsu.edu
2004-12-15
In a quiescent suspension, nanoparticles move randomly and thereby carry relatively large volumes of surrounding liquid with them. This micro-scale interaction may occur between hot and cold regions, resulting in a lower local temperature gradient for a given heat flux compared with the pure liquid case. Thus, as a result of Brownian motion, the effective thermal conductivity, k{sub eff}, which is composed of the particles' conventional static part and the Brownian motion part, increases to result in a lower temperature gradient for a given heat flux. To capture these transport phenomena, a new thermal conductivity model for nanofluids has been developed, which takes the effects of particle size, particle volume fraction and temperature dependence as well as properties of base liquid and particle phase into consideration by considering surrounding liquid traveling with randomly moving nanoparticles.The strong dependence of the effective thermal conductivity on temperature and material properties of both particle and carrier fluid was attributed to the long impact range of the interparticle potential, which influences the particle motion. In the new model, the impact of Brownian motion is more effective at higher temperatures, as also observed experimentally. Specifically, the new model was tested with simple thermal conduction cases, and demonstrated that for a given heat flux, the temperature gradient changes significantly due to a variable thermal conductivity which mainly depends on particle volume fraction, particle size, particle material and temperature. To improve the accuracy and versatility of the k{sub eff}model, more experimental data sets are needed.
Active patterning and asymmetric transport in a model actomyosin network
Energy Technology Data Exchange (ETDEWEB)
Wang, Shenshen [Department of Chemical Engineering and Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Wolynes, Peter G. [Department of Chemistry and Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005 (United States)
2013-12-21
Cytoskeletal networks, which are essentially motor-filament assemblies, play a major role in many developmental processes involving structural remodeling and shape changes. These are achieved by nonequilibrium self-organization processes that generate functional patterns and drive intracellular transport. We construct a minimal physical model that incorporates the coupling between nonlinear elastic responses of individual filaments and force-dependent motor action. By performing stochastic simulations we show that the interplay of motor processes, described as driving anti-correlated motion of the network vertices, and the network connectivity, which determines the percolation character of the structure, can indeed capture the dynamical and structural cooperativity which gives rise to diverse patterns observed experimentally. The buckling instability of individual filaments is found to play a key role in localizing collapse events due to local force imbalance. Motor-driven buckling-induced node aggregation provides a dynamic mechanism that stabilizes the two-dimensional patterns below the apparent static percolation limit. Coordinated motor action is also shown to suppress random thermal noise on large time scales, the two-dimensional configuration that the system starts with thus remaining planar during the structural development. By carrying out similar simulations on a three-dimensional anchored network, we find that the myosin-driven isotropic contraction of a well-connected actin network, when combined with mechanical anchoring that confers directionality to the collective motion, may represent a novel mechanism of intracellular transport, as revealed by chromosome translocation in the starfish oocyte.
Project W-320 thermal hydraulic model benchmarking and baselining
International Nuclear Information System (INIS)
Sathyanarayana, K.
1998-01-01
Project W-320 will be retrieving waste from Tank 241-C-106 and transferring the waste to Tank 241-AY-102. Waste in both tanks must be maintained below applicable thermal limits during and following the waste transfer. Thermal hydraulic process control models will be used for process control of the thermal limits. This report documents the process control models and presents a benchmarking of the models with data from Tanks 241-C-106 and 241-AY-102. Revision 1 of this report will provide a baselining of the models in preparation for the initiation of sluicing
INDIVIDUAL BASED MODELLING APPROACH TO THERMAL ...
Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. Changes in river temperature regimes are producing an additional challenge for upstream migrating adult salmon and steelhead, species that are sensitive to absolute and cumulative thermal exposure. Adult salmon populations have been shown to utilize cold water patches along migration routes when mainstem river temperatures exceed thermal optimums. We are employing an individual based model (IBM) to explore the costs and benefits of spatially-distributed cold water refugia for adult migrating salmon. Our model, developed in the HexSim platform, is built around a mechanistic behavioral decision tree that drives individual interactions with their spatially explicit simulated environment. Population-scale responses to dynamic thermal regimes, coupled with other stressors such as disease and harvest, become emergent properties of the spatial IBM. Other model outputs include arrival times, species-specific survival rates, body energetic content, and reproductive fitness levels. Here, we discuss the challenges associated with parameterizing an individual based model of salmon and steelhead in a section of the Columbia River. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effec
Adaptive thermal modeling of Li-ion batteries
Rad, M.S.; Danilov, D.L.; Baghalha, M.; Kazemeini, M.; Notten, P.H.L.
2013-01-01
An accurate thermal model to predict the heat generation in rechargeable batteries is an essential tool for advanced thermal management in high power applications, such as electric vehicles. For such applications, the battery materials’ details and cell design are normally not provided. In this work
Energy Technology Data Exchange (ETDEWEB)
Fuller, Thomas F. (Georgia Institute of Technology, Atlanta, GA); Bandhauer, Todd (Georgia Institute of Technology, Atlanta, GA); Garimella, Srinivas (Georgia Institute of Technology, Atlanta, GA)
2012-01-01
A fully coupled electrochemical and thermal model for lithium-ion batteries is developed to investigate the impact of different thermal management strategies on battery performance. In contrast to previous modeling efforts focused either exclusively on particle electrochemistry on the one hand or overall vehicle simulations on the other, the present work predicts local electrochemical reaction rates using temperature-dependent data on commercially available batteries designed for high rates (C/LiFePO{sub 4}) in a computationally efficient manner. Simulation results show that conventional external cooling systems for these batteries, which have a low composite thermal conductivity ({approx}1 W/m-K), cause either large temperature rises or internal temperature gradients. Thus, a novel, passive internal cooling system that uses heat removal through liquid-vapor phase change is developed. Although there have been prior investigations of phase change at the microscales, fluid flow at the conditions expected here is not well understood. A first-principles based cooling system performance model is developed and validated experimentally, and is integrated into the coupled electrochemical-thermal model for assessment of performance improvement relative to conventional thermal management strategies. The proposed cooling system passively removes heat almost isothermally with negligible thermal resistances between the heat source and cooling fluid. Thus, the minimization of peak temperatures and gradients within batteries allow increased power and energy densities unencumbered by thermal limitations.
Cyber threat model for tactical radio networks
Kurdziel, Michael T.
2014-05-01
The shift to a full information-centric paradigm in the battlefield has allowed ConOps to be developed that are only possible using modern network communications systems. Securing these Tactical Networks without impacting their capabilities has been a challenge. Tactical networks with fixed infrastructure have similar vulnerabilities to their commercial counterparts (although they need to be secure against adversaries with greater capabilities, resources and motivation). However, networks with mobile infrastructure components and Mobile Ad hoc Networks (MANets) have additional unique vulnerabilities that must be considered. It is useful to examine Tactical Network based ConOps and use them to construct a threat model and baseline cyber security requirements for Tactical Networks with fixed infrastructure, mobile infrastructure and/or ad hoc modes of operation. This paper will present an introduction to threat model assessment. A definition and detailed discussion of a Tactical Network threat model is also presented. Finally, the model is used to derive baseline requirements that can be used to design or evaluate a cyber security solution that can be scaled and adapted to the needs of specific deployments.
Tool wear modeling using abductive networks
Masory, Oren
1992-09-01
A tool wear model based on Abductive Networks, which consists of a network of `polynomial' nodes, is described. The model relates the cutting parameters, components of the cutting force, and machining time to flank wear. Thus real time measurements of the cutting force can be used to monitor the machining process. The model is obtained by a training process in which the connectivity between the network's nodes and the polynomial coefficients of each node are determined by optimizing a performance criteria. Actual wear measurements of coated and uncoated carbide inserts were used for training and evaluating the established model.
Simple models of the thermal structure of the Venusian ionosphere
International Nuclear Information System (INIS)
Whitten, R.C.; Knudsen, W.C.
1980-01-01
Analytical and numerical models of plasma temperatures in the Venusian ionosphere are proposed. The magnitudes of plasma thermal parameters are calculated using thermal-structure data obtained by the Pioneer Venus Orbiter. The simple models are found to be in good agreement with the more detailed models of thermal balance. Daytime and nighttime temperature data along with corresponding temperature profiles are provided
Thermal and Arc Flash Analysis of Electric Motor Drives in Distribution Networks
Nikolovski, Srete; Mlakić, Dragan; Alibašić, Emir
2017-01-01
The paper presents thermal analysis and arc flash analysis taking care of protection relays coordination settings for electric motor drives connected to the electrical network. Power flow analysis is performed to check if there are any voltage and loading violation conditions in the system. Fault analysis is performed to check the short circuit values and compute arc flash energy dissipated at industrial busbars to eliminate damage to electrical equipment and electrical shocks and hazard to p...
Model calculation of thermal conductivity in antiferromagnets
Energy Technology Data Exchange (ETDEWEB)
Mikhail, I.F.I., E-mail: ifi_mikhail@hotmail.com; Ismail, I.M.M.; Ameen, M.
2015-11-01
A theoretical study is given of thermal conductivity in antiferromagnetic materials. The study has the advantage that the three-phonon interactions as well as the magnon phonon interactions have been represented by model operators that preserve the important properties of the exact collision operators. A new expression for thermal conductivity has been derived that involves the same terms obtained in our previous work in addition to two new terms. These two terms represent the conservation and quasi-conservation of wavevector that occur in the three-phonon Normal and Umklapp processes respectively. They gave appreciable contributions to the thermal conductivity and have led to an excellent quantitative agreement with the experimental measurements of the antiferromagnet FeCl{sub 2}. - Highlights: • The Boltzmann equations of phonons and magnons in antiferromagnets have been studied. • Model operators have been used to represent the magnon–phonon and three-phonon interactions. • The models possess the same important properties as the exact operators. • A new expression for the thermal conductivity has been derived. • The results showed a good quantitative agreement with the experimental data of FeCl{sub 2}.
Directory of Open Access Journals (Sweden)
Asif Mahmood
Full Text Available Solar energy is the cleanest, renewable and most abundant source of energy available on earth. The main use of solar energy is to heat and cool buildings, heat water and to generate electricity. There are two types of solar energy collection system, the photovoltaic systems and the solar thermal collectors. The efficiency of any solar thermal system depend on the thermophysical properties of the operating fluids and the geometry/length of the system in which fluid is flowing. In the present research a simplified mathematical model for the solar thermal collectors is considered in the form of non-uniform unsteady stretching surface. The flow is induced by a non-uniform stretching of the porous sheet and the uniform magnetic field is applied in the transverse direction to the flow. The non-Newtonian Maxwell fluid model is utilized for the working fluid along with slip boundary conditions. Moreover the high temperature effect of thermal radiation and temperature dependent thermal conductivity are also included in the present model. The mathematical formulation is carried out through a boundary layer approach and the numerical computations are carried out for cu-water and TiO2-water nanofluids. Results are presented for the velocity and temperature profiles as well as the skin friction coefficient and Nusselt number and the discussion is concluded on the effect of various governing parameters on the motion, temperature variation, velocity gradient and the rate of heat transfer at the boundary. Keywords: Solar energy, Thermal collectors, Maxwell-nanofluid, Thermal radiation, Partial slip, Variable thermal conductivity
Biological transportation networks: Modeling and simulation
Albi, Giacomo; Artina, Marco; Foransier, Massimo; Markowich, Peter A.
2015-01-01
We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation
Synergistic effects in threshold models on networks
Juul, Jonas S.; Porter, Mason A.
2018-01-01
Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can—depending on a parameter—either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.
Modeling geomagnetic induced currents in Australian power networks
Marshall, R. A.; Kelly, A.; Van Der Walt, T.; Honecker, A.; Ong, C.; Mikkelsen, D.; Spierings, A.; Ivanovich, G.; Yoshikawa, A.
2017-07-01
Geomagnetic induced currents (GICs) have been considered an issue for high-latitude power networks for some decades. More recently, GICs have been observed and studied in power networks located in lower latitude regions. This paper presents the results of a model aimed at predicting and understanding the impact of geomagnetic storms on power networks in Australia, with particular focus on the Queensland and Tasmanian networks. The model incorporates a "geoelectric field" determined using a plane wave magnetic field incident on a uniform conducting Earth, and the network model developed by Lehtinen and Pirjola (1985). Model results for two intense geomagnetic storms of solar cycle 24 are compared with transformer neutral monitors at three locations within the Queensland network and one location within the Tasmanian network. The model is then used to assess the impacts of the superintense geomagnetic storm of 29-31 October 2003 on the flow of GICs within these networks. The model results show good correlation with the observations with coefficients ranging from 0.73 to 0.96 across the observing sites. For Queensland, modeled GIC magnitudes during the superstorm of 29-31 October 2003 exceed 40 A with the larger GICs occurring in the south-east section of the network. Modeled GICs in Tasmania for the same storm do not exceed 30 A. The larger distance spans and general east-west alignment of the southern section of the Queensland network, in conjunction with some relatively low branch resistance values, result in larger modeled GICs despite Queensland being a lower latitude network than Tasmania.
Modeling Distillation Column Using ARX Model Structure and Artificial Neural Networks
Directory of Open Access Journals (Sweden)
Reza Pirmoradi
2012-04-01
Full Text Available Distillation is a complex and highly nonlinear industrial process. In general it is not always possible to obtain accurate first principles models for high-purity distillation columns. On the other hand the development of first principles models is usually time consuming and expensive. To overcome these problems, empirical models such as neural networks can be used. One major drawback of empirical models is that the prediction is valid only inside the data domain that is sufficiently covered by measurement data. Modeling distillation columns by means of neural networks is reported in literature by using recursive networks. The recursive networks are proper for modeling purpose, but such models have the problems of high complexity and high computational cost. The objective of this paper is to propose a simple and reliable model for distillation column. The proposed model uses feed forward neural networks which results in a simple model with less parameters and faster training time. Simulation results demonstrate that predictions of the proposed model in all regions are close to outputs of the dynamic model and the error in negligible. This implies that the model is reliable in all regions.
Harvey, Jason; Moore, Michael
2013-01-01
The General-Use Nodal Network Solver (GUNNS) is a modeling software package that combines nodal analysis and the hydraulic-electric analogy to simulate fluid, electrical, and thermal flow systems. GUNNS is developed by L-3 Communications under the TS21 (Training Systems for the 21st Century) project for NASA Johnson Space Center (JSC), primarily for use in space vehicle training simulators at JSC. It has sufficient compactness and fidelity to model the fluid, electrical, and thermal aspects of space vehicles in real-time simulations running on commodity workstations, for vehicle crew and flight controller training. It has a reusable and flexible component and system design, and a Graphical User Interface (GUI), providing capability for rapid GUI-based simulator development, ease of maintenance, and associated cost savings. GUNNS is optimized for NASA's Trick simulation environment, but can be run independently of Trick.
Modeling of Viscosity and Thermal Expansion of Bioactive Glasses
Farid, Saad B. H.
2012-01-01
The behaviors of viscosity and thermal expansion for different compositions of bioactive glasses have been studied. The effect of phosphorous pentoxide as a second glass former in addition to silica was investigated. Consequently, the nonlinear behaviors of viscosity and thermal expansion with respect to the oxide composition have been modeled. The modeling uses published data on bioactive glass compositions with viscosity and thermal expansion. -regression optimization technique has been uti...
Frank, Laurence Emmanuelle
2006-01-01
Feature Network Models (FNM) are graphical structures that represent proximity data in a discrete space with the use of features. A statistical inference theory is introduced, based on the additivity properties of networks and the linear regression framework. Considering features as predictor
Quantifying the relevance of adaptive thermal comfort models in moderate thermal climate zones
Hoof, van J.; Hensen, J.L.M.
2007-01-01
Standards governing thermal comfort evaluation are on a constant cycle of revision and public review. One of the main topics being discussed in the latest round was the introduction of an adaptive thermal comfort model, which now forms an optional part of ASHRAE Standard 55. Also on a national
A hybrid optimization model of biomass trigeneration system combined with pit thermal energy storage
International Nuclear Information System (INIS)
Dominković, D.F.; Ćosić, B.; Bačelić Medić, Z.; Duić, N.
2015-01-01
Highlights: • Hybrid optimization model of biomass trigeneration system with PTES is developed. • Influence of premium feed-in tariffs on trigeneration systems is assessed. • Influence of total system efficiency on biomass trigeneration system with PTES is assessed. • Influence of energy savings on project economy is assessed. - Abstract: This paper provides a solution for managing excess heat production in trigeneration and thus, increases the power plant yearly efficiency. An optimization model for combining biomass trigeneration energy system and pit thermal energy storage has been developed. Furthermore, double piping district heating and cooling network in the residential area without industry consumers was assumed, thus allowing simultaneous flow of the heating and cooling energy. As a consequence, the model is easy to adopt in different regions. Degree-hour method was used for calculation of hourly heating and cooling energy demand. The system covers all the yearly heating and cooling energy needs, while it is assumed that all the electricity can be transferred to the grid due to its renewable origin. The system was modeled in Matlab© on hourly basis and hybrid optimization model was used to maximize the net present value (NPV), which was the objective function of the optimization. Economic figures become favorable if the economy-of-scale of both power plant and pit thermal energy storage can be utilized. The results show that the pit thermal energy storage was an excellent option for storing energy and shaving peaks in energy demand. Finally, possible switch from feed-in tariffs to feed-in premiums was assessed and possible subsidy savings have been calculated. The savings are potentially large and can be used for supporting other renewable energy projects
Nonparametric Bayesian Modeling of Complex Networks
DEFF Research Database (Denmark)
Schmidt, Mikkel Nørgaard; Mørup, Morten
2013-01-01
an infinite mixture model as running example, we go through the steps of deriving the model as an infinite limit of a finite parametric model, inferring the model parameters by Markov chain Monte Carlo, and checking the model?s fit and predictive performance. We explain how advanced nonparametric models......Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...
Modelling and designing electric energy networks
International Nuclear Information System (INIS)
Retiere, N.
2003-11-01
The author gives an overview of his research works in the field of electric network modelling. After a brief overview of technological evolutions from the telegraph to the all-electric fly-by-wire aircraft, he reports and describes various works dealing with a simplified modelling of electric systems and with fractal simulation. Then, he outlines the challenges for the design of electric networks, proposes a design process, gives an overview of various design models, methods and tools, and reports an application in the design of electric networks for future jumbo jets
Modelling traffic congestion using queuing networks
Indian Academy of Sciences (India)
Flow-density curves; uninterrupted traffic; Jackson networks. ... ness - also suffer from a big handicap vis-a-vis the Indian scenario: most of these models do .... more well-known queuing network models and onsite data, a more exact Road Cell ...
Thermal conductivity model of vibro-packed fuel
International Nuclear Information System (INIS)
Yeon Soo, Kim
2001-01-01
In an effort to dispose of excess weapons grade plutonium accumulated in the cold war era in the United States and the Russian Federation, one method currently under investigation is the conversion of the plutonium into mixed oxide (MOX) reactor fuel for LWRs and fast reactors in the Russian Federation. A fuel option already partly developed at the Research Institute of Atomic Reactors (RIAR) in Dimitrovgrad is that of vibro-packed MOX. Fuel rod fabrication using powder vibro-packing is attractive because it includes neither a process too complex to operate in glove boxes (or remotely), nor a waste-producing step necessary for the conventional pellet rod fabrication. However, because of its loose bonding between fuel particles at the beginning of life, vibro-packed MOX fuel has a somewhat less effective thermal conductivity than fully sintered pellet fuel, and undergoes more restructuring. Helium would also likely be pressurized in vibro-packed MOX fuel rods for LWRs to enhance initial fuel thermal conductivity. The combination of these two factors complicates development of an accurate thermal conductivity model. But clearly in order to predict fuel thermomechanical responses during irradiation of vibro-packed MOX fuel, fuel thermal conductivity must be known. The Vibropac fuel of interest in this study refers the fuel that is compacted with irregular fragments of mixed oxide fuel. In this paper, the thermal-conductivity models in the literature that dealt with relatively similar situations to the present case are examined. Then, the best model is selected based on accuracy of prediction and applicability. Then, the selected model is expanded to fit the various situations of interest. (author)
Recurrent neural network based hybrid model for reconstructing gene regulatory network.
Raza, Khalid; Alam, Mansaf
2016-10-01
One of the exciting problems in systems biology research is to decipher how genome controls the development of complex biological system. The gene regulatory networks (GRNs) help in the identification of regulatory interactions between genes and offer fruitful information related to functional role of individual gene in a cellular system. Discovering GRNs lead to a wide range of applications, including identification of disease related pathways providing novel tentative drug targets, helps to predict disease response, and also assists in diagnosing various diseases including cancer. Reconstruction of GRNs from available biological data is still an open problem. This paper proposes a recurrent neural network (RNN) based model of GRN, hybridized with generalized extended Kalman filter for weight update in backpropagation through time training algorithm. The RNN is a complex neural network that gives a better settlement between biological closeness and mathematical flexibility to model GRN; and is also able to capture complex, non-linear and dynamic relationships among variables. Gene expression data are inherently noisy and Kalman filter performs well for estimation problem even in noisy data. Hence, we applied non-linear version of Kalman filter, known as generalized extended Kalman filter, for weight update during RNN training. The developed model has been tested on four benchmark networks such as DNA SOS repair network, IRMA network, and two synthetic networks from DREAM Challenge. We performed a comparison of our results with other state-of-the-art techniques which shows superiority of our proposed model. Further, 5% Gaussian noise has been induced in the dataset and result of the proposed model shows negligible effect of noise on results, demonstrating the noise tolerance capability of the model. Copyright © 2016 Elsevier Ltd. All rights reserved.
Modeling directional thermal radiance from a forest canopy
International Nuclear Information System (INIS)
McGuire, M.J.; Balick, L.K.; Smith, J.A.; Hutchison, B.A.
1989-01-01
Recent advances in remote sensing technology have increased interest in utilizing the thermal-infared region to gain additional information about surface features such as vegetation canopies. Studies have shown that sensor view angle, canopy structure, and percentage of canopy coverage can affect the response of a thermal sensor. These studies have been primarily of agricultural regions and there have been relatively few examples describing the thermal characteristics of forested regions. This paper describes an extension of an existing thermal vegetation canopy radiance model which has been modified to partially account for the geometrically rough structure of a forest canopy. Fourier series expansion of a canopy height profile is used to calculate improved view factors which partially account for the directional variations in canopy thermal radiance transfers. The original and updated radiance model predictions are compared with experimental data obtained over a deciduous (oak-hickory) forest site. The experimental observations are also used to document azimuthal and nadir directional radiance variations. Maximum angular variations in measured canopy temperatures were 4–6°C (azimuth) and 2.5°C (nadir). Maximum angular variations in simulated temperatures using the modified rough surface model was 4°C. The rough surface model appeared to be sensitive to large gaps in the canopy height profile, which influenced the resultant predicted temperature. (author)
Lawson, John W.; Daw, Murray S.; Squire, Thomas H.; Bauschlicher, Charles W.
2012-01-01
We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.
Modeling, Optimization & Control of Hydraulic Networks
DEFF Research Database (Denmark)
Tahavori, Maryamsadat
2014-01-01
. The nonlinear network model is derived based on the circuit theory. A suitable projection is used to reduce the state vector and to express the model in standard state-space form. Then, the controllability of nonlinear nonaffine hydraulic networks is studied. The Lie algebra-based controllability matrix is used......Water supply systems consist of a number of pumping stations, which deliver water to the customers via pipeline networks and elevated reservoirs. A huge amount of drinking water is lost before it reaches to end-users due to the leakage in pipe networks. A cost effective solution to reduce leakage...... in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply...
Strangeness by Thermal Model Simulation at RHIC
Institute of Scientific and Technical Information of China (English)
SHI Xing-Hua; MA Yu-Gang; CAI Xiang-Zhou; CHEN Jin-Hui; MA Guo-Liang; ZHONG Chen
2009-01-01
The local temperature effect on strangeness enhancement in relativistic heavy ion collisions is discussed in the framework of the thermal model in which the K+ /h+ ratio becomes smaller with increasing freeze-out temperature.Considering that most strangeness particles of final-state particles are from the kaon meson,the temperature effect may play a role in strangeness production in hot dense matter where a slightly different temperature distribution in different areas could be produced by jet energy loss.This phenomenon is predicted by thermal model calculation at RHIC energy.The Ε-/φ ratio in central Au+Au collisions at 200 GeV from the thermal model depends on the freeze-out temperature obviously when γs is different.It should be one of the reasons why strangeness enhancements of Ε and φ are different though they include two strange quarks.These results indicate that thermodynamics is an important factor for strangeness production and the strangeness enhancement phenomenon.
Evaluation of Thermal Margin Analysis Models for SMART
International Nuclear Information System (INIS)
Seo, Kyong Won; Kwon, Hyuk; Hwang, Dae Hyun
2011-01-01
Thermal margin of SMART would be analyzed by three different methods. The first method is subchannel analysis by MATRA-S code and it would be a reference data for the other two methods. The second method is an on-line few channel analysis by FAST code that would be integrated into SCOPS/SCOMS. The last one is a single channel module analysis by safety analysis. Several thermal margin analysis models for SMART reactor core by subchannel analysis were setup and tested. We adopted a strategy of single stage analysis for thermal analysis of SMART reactor core. The model should represent characteristics of the SMART reactor core including hot channel. The model should be simple as possible to be evaluated within reasonable time and cost
Coupling of the Models of Human Physiology and Thermal Comfort
Pokorny, J.; Jicha, M.
2013-04-01
A coupled model of human physiology and thermal comfort was developed in Dymola/Modelica. A coupling combines a modified Tanabe model of human physiology and thermal comfort model developed by Zhang. The Coupled model allows predicting the thermal sensation and comfort of both local and overall from local boundary conditions representing ambient and personal factors. The aim of this study was to compare prediction of the Coupled model with the Fiala model prediction and experimental data. Validation data were taken from the literature, mainly from the validation manual of software Theseus-FE [1]. In the paper validation of the model for very light physical activities (1 met) indoor environment with temperatures from 12 °C up to 48 °C is presented. The Coupled model predicts mean skin temperature for cold, neutral and warm environment well. However prediction of core temperature in cold environment is inaccurate and very affected by ambient temperature. Evaluation of thermal comfort in warm environment is supplemented by skin wettedness prediction. The Coupled model is designed for non-uniform and transient environmental conditions; it is also suitable simulation of thermal comfort in vehicles cabins. The usage of the model is limited for very light physical activities up to 1.2 met only.
Coupling of the Models of Human Physiology and Thermal Comfort
Directory of Open Access Journals (Sweden)
Jicha M.
2013-04-01
Full Text Available A coupled model of human physiology and thermal comfort was developed in Dymola/Modelica. A coupling combines a modified Tanabe model of human physiology and thermal comfort model developed by Zhang. The Coupled model allows predicting the thermal sensation and comfort of both local and overall from local boundary conditions representing ambient and personal factors. The aim of this study was to compare prediction of the Coupled model with the Fiala model prediction and experimental data. Validation data were taken from the literature, mainly from the validation manual of software Theseus–FE [1]. In the paper validation of the model for very light physical activities (1 met indoor environment with temperatures from 12 °C up to 48 °C is presented. The Coupled model predicts mean skin temperature for cold, neutral and warm environment well. However prediction of core temperature in cold environment is inaccurate and very affected by ambient temperature. Evaluation of thermal comfort in warm environment is supplemented by skin wettedness prediction. The Coupled model is designed for non-uniform and transient environmental conditions; it is also suitable simulation of thermal comfort in vehicles cabins. The usage of the model is limited for very light physical activities up to 1.2 met only.
A random spatial network model based on elementary postulates
Karlinger, Michael R.; Troutman, Brent M.
1989-01-01
A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.
Modeling Network Traffic in Wavelet Domain
Directory of Open Access Journals (Sweden)
Sheng Ma
2004-12-01
Full Text Available This work discovers that although network traffic has the complicated short- and long-range temporal dependence, the corresponding wavelet coefficients are no longer long-range dependent. Therefore, a "short-range" dependent process can be used to model network traffic in the wavelet domain. Both independent and Markov models are investigated. Theoretical analysis shows that the independent wavelet model is sufficiently accurate in terms of the buffer overflow probability for Fractional Gaussian Noise traffic. Any model, which captures additional correlations in the wavelet domain, only improves the performance marginally. The independent wavelet model is then used as a unified approach to model network traffic including VBR MPEG video and Ethernet data. The computational complexity is O(N for developing such wavelet models and generating synthesized traffic of length N, which is among the lowest attained.
Reactor Thermal Hydraulic Numerical Calculation And Modeling
International Nuclear Information System (INIS)
Duong Ngoc Hai; Dang The Ba
2008-01-01
In the paper the results of analysis of thermal hydraulic state models using the numerical codes such as COOLOD, EUREKA and RELAP5 for simulation of the reactor thermal hydraulic states are presented. The calculations, analyses of reactor thermal hydraulic state and safety were implemented using different codes. The received numerical results, which were compared each to other, to experiment measurement of Dalat (Vietnam) research reactor and published results, show their appropriateness and capacity for analyses of different appropriate cases. (author)
Directory of Open Access Journals (Sweden)
Lan Liu
2017-01-01
Full Text Available As the adoption of Software Defined Networks (SDNs grows, the security of SDN still has several unaddressed limitations. A key network security research area is in the study of malware propagation across the SDN-enabled networks. To analyze the spreading processes of network malware (e.g., viruses in SDN, we propose a dynamic model with a time-varying community network, inspired by research models on the spread of epidemics in complex networks across communities. We assume subnets of the network as communities and links that are dense in subnets but sparse between subnets. Using numerical simulation and theoretical analysis, we find that the efficiency of network malware propagation in this model depends on the mobility rate q of the nodes between subnets. We also find that there exists a mobility rate threshold qc. The network malware will spread in the SDN when the mobility rate q>qc. The malware will survive when q>qc and perish when q
Creating, generating and comparing random network models with NetworkRandomizer.
Tosadori, Gabriele; Bestvina, Ivan; Spoto, Fausto; Laudanna, Carlo; Scardoni, Giovanni
2016-01-01
Biological networks are becoming a fundamental tool for the investigation of high-throughput data in several fields of biology and biotechnology. With the increasing amount of information, network-based models are gaining more and more interest and new techniques are required in order to mine the information and to validate the results. To fill the validation gap we present an app, for the Cytoscape platform, which aims at creating randomised networks and randomising existing, real networks. Since there is a lack of tools that allow performing such operations, our app aims at enabling researchers to exploit different, well known random network models that could be used as a benchmark for validating real, biological datasets. We also propose a novel methodology for creating random weighted networks, i.e. the multiplication algorithm, starting from real, quantitative data. Finally, the app provides a statistical tool that compares real versus randomly computed attributes, in order to validate the numerical findings. In summary, our app aims at creating a standardised methodology for the validation of the results in the context of the Cytoscape platform.
Investigation of transient thermal dissipation in thinned LSI for advanced packaging
Araga, Yuuki; Shimamoto, Haruo; Melamed, Samson; Kikuchi, Katsuya; Aoyagi, Masahiro
2018-04-01
Thinning of LSI is necessary for superior form factor and performance in dense cutting-edge packaging technologies. At the same time, degradation of thermal characteristics caused by the steep thermal gradient on LSIs with thinned base silicon is a concern. To manage a thermal environment in advanced packages, thermal characteristics of the thinned LSIs must be clarified. In this study, static and dynamic thermal dissipations were analyzed before and after thinning silicon to determine variations of thermal characteristics in thinned LSI. Measurement results revealed that silicon thinning affects dynamic thermal characteristics as well as static one. The transient variations of thermal characteristics of thinned LSI are precisely verified by analysis using an equivalent model based on the thermal network method. The results of analysis suggest that transient thermal characteristics can be easily estimated by employing the equivalent model.
Thermal-Chemical Model Of Subduction: Results And Tests
Gorczyk, W.; Gerya, T. V.; Connolly, J. A.; Yuen, D. A.; Rudolph, M.
2005-12-01
Seismic structures with strong positive and negative velocity anomalies in the mantle wedge above subduction zones have been interpreted as thermally and/or chemically induced phenomena. We have developed a thermal-chemical model of subduction, which constrains the dynamics of seismic velocity structure beneath volcanic arcs. Our simulations have been calculated over a finite-difference grid with (201×101) to (201×401) regularly spaced Eulerian points, using 0.5 million to 10 billion markers. The model couples numerical thermo-mechanical solution with Gibbs energy minimization to investigate the dynamic behavior of partially molten upwellings from slabs (cold plumes) and structures associated with their development. The model demonstrates two chemically distinct types of plumes (mixed and unmixed), and various rigid body rotation phenomena in the wedge (subduction wheel, fore-arc spin, wedge pin-ball). These thermal-chemical features strongly perturb seismic structure. Their occurrence is dependent on the age of subducting slab and the rate of subduction.The model has been validated through a series of test cases and its results are consistent with a variety of geological and geophysical data. In contrast to models that attribute a purely thermal origin for mantle wedge seismic anomalies, the thermal-chemical model is able to simulate the strong variations of seismic velocity existing beneath volcanic arcs which are associated with development of cold plumes. In particular, molten regions that form beneath volcanic arcs as a consequence of vigorous cold wet plumes are manifest by > 20% variations in the local Poisson ratio, as compared to variations of ~ 2% expected as a consequence of temperature variation within the mantle wedge.
Thermal hydraulic model validation for HOR mixed core fuel management
International Nuclear Information System (INIS)
Gibcus, H.P.M.; Vries, J.W. de; Leege, P.F.A. de
1997-01-01
A thermal-hydraulic core management model has been developed for the Hoger Onderwijsreactor (HOR), a 2 MW pool-type university research reactor. The model was adopted for safety analysis purposes in the framework of HEU/LEU core conversion studies. It is applied in the thermal-hydraulic computer code SHORT (Steady-state HOR Thermal-hydraulics) which is presently in use in designing core configurations and for in-core fuel management. An elaborate measurement program was performed for establishing the core hydraulic characteristics for a variety of conditions. The hydraulic data were obtained with a dummy fuel element with special equipment allowing a.o. direct measurement of the true core flow rate. Using these data the thermal-hydraulic model was validated experimentally. The model, experimental tests, and model validation are discussed. (author)
An anisotropic thermal-stress model for through-silicon via
Liu, Song; Shan, Guangbao
2018-02-01
A two-dimensional thermal-stress model of through-silicon via (TSV) is proposed considering the anisotropic elastic property of the silicon substrate. By using the complex variable approach, the distribution of thermal-stress in the substrate can be characterized more accurately. TCAD 3-D simulations are used to verify the model accuracy and well agree with analytical results (model can be integrated into stress-driven design flow for 3-D IC , leading to the more accurate timing analysis considering the thermal-stress effect. Project supported by the Aerospace Advanced Manufacturing Technology Research Joint Fund (No. U1537208).
Thermal model of spent fuel transport cask
International Nuclear Information System (INIS)
Ahmed, E.E.M.; Rahman, F.A.; Sultan, G.F.; Khalil, E.E.
1996-01-01
The investigation provides a theoretical model to represent the thermal behaviour of the spent fuel elements when transported in a dry shipping cask under normal transport conditions. The heat transfer process in the spent fuel elements and within the cask are modeled which include the radiant heat transfer within the cask and the heat transfer by thermal conduction within the spent fuel element. The model considers the net radiant method for radiant heat transfer process from the inner most heated element to the surrounding spent elements. The heat conduction through fuel interior, fuel-clad interface and on clad surface are also presented. (author) 6 figs., 9 refs
Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks
Directory of Open Access Journals (Sweden)
Liang Jinghang
2012-08-01
Full Text Available Abstract Background Various computational models have been of interest due to their use in the modelling of gene regulatory networks (GRNs. As a logical model, probabilistic Boolean networks (PBNs consider molecular and genetic noise, so the study of PBNs provides significant insights into the understanding of the dynamics of GRNs. This will ultimately lead to advances in developing therapeutic methods that intervene in the process of disease development and progression. The applications of PBNs, however, are hindered by the complexities involved in the computation of the state transition matrix and the steady-state distribution of a PBN. For a PBN with n genes and N Boolean networks, the complexity to compute the state transition matrix is O(nN22n or O(nN2n for a sparse matrix. Results This paper presents a novel implementation of PBNs based on the notions of stochastic logic and stochastic computation. This stochastic implementation of a PBN is referred to as a stochastic Boolean network (SBN. An SBN provides an accurate and efficient simulation of a PBN without and with random gene perturbation. The state transition matrix is computed in an SBN with a complexity of O(nL2n, where L is a factor related to the stochastic sequence length. Since the minimum sequence length required for obtaining an evaluation accuracy approximately increases in a polynomial order with the number of genes, n, and the number of Boolean networks, N, usually increases exponentially with n, L is typically smaller than N, especially in a network with a large number of genes. Hence, the computational efficiency of an SBN is primarily limited by the number of genes, but not directly by the total possible number of Boolean networks. Furthermore, a time-frame expanded SBN enables an efficient analysis of the steady-state distribution of a PBN. These findings are supported by the simulation results of a simplified p53 network, several randomly generated networks and a
Network interconnections: an architectural reference model
Butscher, B.; Lenzini, L.; Morling, R.; Vissers, C.A.; Popescu-Zeletin, R.; van Sinderen, Marten J.; Heger, D.; Krueger, G.; Spaniol, O.; Zorn, W.
1985-01-01
One of the major problems in understanding the different approaches in interconnecting networks of different technologies is the lack of reference to a general model. The paper develops the rationales for a reference model of network interconnection and focuses on the architectural implications for
Thermal hydraulic model descrition of TASS/SMR
Energy Technology Data Exchange (ETDEWEB)
Yoon, Han Young; Kim, H. C.; Chung, Y. J.; Lim, H. S.; Yang, S. H
2001-04-01
The TASS/SMR code has been developed for the safety analysis of SMART. The governing equations were applied only to the primary coolant system in TASS which had been developed at KAERI. In TASS/SMR, the solution method is improved so that the primary and secondary coolant systems are solved simultaneously. Besides the solution method, thermal-hydraulic models are incorporated, in TASS/SMR, such as non-condensible gas model, helical steam generator heat transfer model, and passive residual heat removal system (PRHRS) heat transfer model for the application to SMART. The governing equtions of TASS/SMR are based on the drift-flux model so that the accidents and transients accompaning with two-phase flow can be analized. This report describes the governing equations and solution methods used in TASS/SMR and also includes the description for the thermal hydraulic models for SMART design.
A general evolving model for growing bipartite networks
International Nuclear Information System (INIS)
Tian, Lixin; He, Yinghuan; Liu, Haijun; Du, Ruijin
2012-01-01
In this Letter, we propose and study an inner evolving bipartite network model. Significantly, we prove that the degree distribution of two different kinds of nodes both obey power-law form with adjustable exponents. Furthermore, the joint degree distribution of any two nodes for bipartite networks model is calculated analytically by the mean-field method. The result displays that such bipartite networks are nearly uncorrelated networks, which is different from one-mode networks. Numerical simulations and empirical results are given to verify the theoretical results. -- Highlights: ► We proposed a general evolving bipartite network model which was based on priority connection, reconnection and breaking edges. ► We prove that the degree distribution of two different kinds of nodes both obey power-law form with adjustable exponents. ► The joint degree distribution of any two nodes for bipartite networks model is calculated analytically by the mean-field method. ► The result displays that such bipartite networks are nearly uncorrelated networks, which is different from one-mode networks.
Model of community emergence in weighted social networks
Kumpula, J. M.; Onnela, J.-P.; Saramäki, J.; Kertész, J.; Kaski, K.
2009-04-01
Over the years network theory has proven to be rapidly expanding methodology to investigate various complex systems and it has turned out to give quite unparalleled insight to their structure, function, and response through data analysis, modeling, and simulation. For social systems in particular the network approach has empirically revealed a modular structure due to interplay between the network topology and link weights between network nodes or individuals. This inspired us to develop a simple network model that could catch some salient features of mesoscopic community and macroscopic topology formation during network evolution. Our model is based on two fundamental mechanisms of network sociology for individuals to find new friends, namely cyclic closure and focal closure, which are mimicked by local search-link-reinforcement and random global attachment mechanisms, respectively. In addition we included to the model a node deletion mechanism by removing all its links simultaneously, which corresponds for an individual to depart from the network. Here we describe in detail the implementation of our model algorithm, which was found to be computationally efficient and produce many empirically observed features of large-scale social networks. Thus this model opens a new perspective for studying such collective social phenomena as spreading, structure formation, and evolutionary processes.
Thermal modeling: at the crossroads of several subjects of physics
International Nuclear Information System (INIS)
1997-01-01
The modeling of thermal phenomena is of prime importance for the dimensioning of industrial facilities. However, the understanding of thermal processes requires to refer to other subjects of physics like electromagnetism, matter transformation, fluid mechanics, chemistry etc.. The aim of this workshop organized by the industrial electro-thermal engineering section of the French society of thermal engineers is to take stock of current or forthcoming advances in the coupling of thermal engineering codes with electromagnetic, fluid mechanics, chemical and mechanical engineering codes. The modeling of phenomena remains the essential link between the laboratory research of new processes and their industrial developments. From the 9 talks given during this workshop, 2 of them deal with thermal processes in nuclear reactors and fall into the INIS scope and the others concern the modeling of industrial heating or electrical processes and were selected for ETDE. (J.S.)
Visser, Philip W.; Kooi, Henk; Stuyfzand, Pieter J.
2015-05-01
Results are presented of a comprehensive thermal impact study on an aquifer thermal energy storage (ATES) system in Bilthoven, the Netherlands. The study involved monitoring of the thermal impact and modeling of the three-dimensional temperature evolution of the storage aquifer and over- and underlying units. Special attention was paid to non-uniformity of the background temperature, which varies laterally and vertically in the aquifer. Two models were applied with different levels of detail regarding initial conditions and heterogeneity of hydraulic and thermal properties: a fine-scale heterogeneity model which construed the lateral and vertical temperature distribution more realistically, and a simplified model which represented the aquifer system with only a limited number of homogeneous layers. Fine-scale heterogeneity was shown to be important to accurately model the ATES-impacted vertical temperature distribution and the maximum and minimum temperatures in the storage aquifer, and the spatial extent of the thermal plumes. The fine-scale heterogeneity model resulted in larger thermally impacted areas and larger temperature anomalies than the simplified model. The models showed that scattered and scarce monitoring data of ATES-induced temperatures can be interpreted in a useful way by groundwater and heat transport modeling, resulting in a realistic assessment of the thermal impact.
A quantum-implementable neural network model
Chen, Jialin; Wang, Lingli; Charbon, Edoardo
2017-10-01
A quantum-implementable neural network, namely quantum probability neural network (QPNN) model, is proposed in this paper. QPNN can use quantum parallelism to trace all possible network states to improve the result. Due to its unique quantum nature, this model is robust to several quantum noises under certain conditions, which can be efficiently implemented by the qubus quantum computer. Another advantage is that QPNN can be used as memory to retrieve the most relevant data and even to generate new data. The MATLAB experimental results of Iris data classification and MNIST handwriting recognition show that much less neuron resources are required in QPNN to obtain a good result than the classical feedforward neural network. The proposed QPNN model indicates that quantum effects are useful for real-life classification tasks.
Modeling acquaintance networks based on balance theory
Directory of Open Access Journals (Sweden)
Vukašinović Vida
2014-09-01
Full Text Available An acquaintance network is a social structure made up of a set of actors and the ties between them. These ties change dynamically as a consequence of incessant interactions between the actors. In this paper we introduce a social network model called the Interaction-Based (IB model that involves well-known sociological principles. The connections between the actors and the strength of the connections are influenced by the continuous positive and negative interactions between the actors and, vice versa, the future interactions are more likely to happen between the actors that are connected with stronger ties. The model is also inspired by the social behavior of animal species, particularly that of ants in their colony. A model evaluation showed that the IB model turned out to be sparse. The model has a small diameter and an average path length that grows in proportion to the logarithm of the number of vertices. The clustering coefficient is relatively high, and its value stabilizes in larger networks. The degree distributions are slightly right-skewed. In the mature phase of the IB model, i.e., when the number of edges does not change significantly, most of the network properties do not change significantly either. The IB model was found to be the best of all the compared models in simulating the e-mail URV (University Rovira i Virgili of Tarragona network because the properties of the IB model more closely matched those of the e-mail URV network than the other models
Mathematical Modelling Plant Signalling Networks
Muraro, D.
2013-01-01
During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more comprehensive modelling studies of hormonal transport and signalling in a multi-scale setting. © EDP Sciences, 2013.
Ripple-Spreading Network Model Optimization by Genetic Algorithm
Directory of Open Access Journals (Sweden)
Xiao-Bing Hu
2013-01-01
Full Text Available Small-world and scale-free properties are widely acknowledged in many real-world complex network systems, and many network models have been developed to capture these network properties. The ripple-spreading network model (RSNM is a newly reported complex network model, which is inspired by the natural ripple-spreading phenomenon on clam water surface. The RSNM exhibits good potential for describing both spatial and temporal features in the development of many real-world networks where the influence of a few local events spreads out through nodes and then largely determines the final network topology. However, the relationships between ripple-spreading related parameters (RSRPs of RSNM and small-world and scale-free topologies are not as obvious or straightforward as in many other network models. This paper attempts to apply genetic algorithm (GA to tune the values of RSRPs, so that the RSNM may generate these two most important network topologies. The study demonstrates that, once RSRPs are properly tuned by GA, the RSNM is capable of generating both network topologies and therefore has a great flexibility to study many real-world complex network systems.
International Nuclear Information System (INIS)
Bahiraei, Farid; Fartaj, Amir; Nazri, Gholam-Abbas
2017-01-01
Lithium-ion batteries are commonly used in hybrid electric and full electric vehicles (HEV and EV). In HEV, thermal management is a strict requirement to control the batteries temperature within an optimal range in order to enhance performance, safety, reduce cost, and prolong the batteries lifetime. The optimum design of a thermal management system depends on the thermo-electrochemical behavior of the batteries, operating conditions, and weight and volume constraints. The aim of this study is to investigate the effects of various operating and design parameters on the thermal performance of a battery module consisted of six building block cells. An electrochemical-thermal model coupled to conjugate heat transfer and fluid dynamics simulations is used to assess the effectiveness of two indirect liquid thermal management approaches under the FUDC driving cycle. In this study, a novel pseudo 3D electrochemical-thermal model of the battery is used. It is found that the cooling plate thickness has a significant effect on the maximum and gradient of temperature in the module. Increasing the Reynolds number decreases the average temperature but at the expense of temperature uniformity. The results show that double channel cooling system has a lower maximum temperature and more uniform temperature distribution compared to a single channel cooling system.
Numerical modeling of the autumnal thermal bar
Tsydenov, Bair O.
2018-03-01
The autumnal riverine thermal bar of Kamloops Lake has been simulated using atmospheric data from December 1, 2015, to January 4, 2016. The nonhydrostatic 2.5D mathematical model developed takes into account the diurnal variability of the heat fluxes and wind on the lake surface. The average values for shortwave and longwave radiation and latent and sensible heat fluxes were 19.7 W/m2, - 95.9 W/m2, - 11.8 W/m2, and - 32.0 W/m2 respectively. Analysis of the wind regime data showed prevailing easterly winds and maximum speed of 11 m/s on the 8th and 19th days. Numerical experiments with different boundary conditions at the lake surface were conducted to evaluate effects of variable heat flux and wind stress. The results of modeling demonstrated that the variable heat flux affects the process of thermal bar evolution, especially during the lengthy night cooling. However, the wind had the greatest impact on the behavior of the autumnal thermal bar: The easterly winds contributed to an earlier appearance of the thermal bar, but the strong winds generating the intensive circulations (the velocity of the upper lake flow increased to 6 cm/s) may destroy the thermal bar front.
Constitutive modelling of composite biopolymer networks.
Fallqvist, B; Kroon, M
2016-04-21
The mechanical behaviour of biopolymer networks is to a large extent determined at a microstructural level where the characteristics of individual filaments and the interactions between them determine the response at a macroscopic level. Phenomena such as viscoelasticity and strain-hardening followed by strain-softening are observed experimentally in these networks, often due to microstructural changes (such as filament sliding, rupture and cross-link debonding). Further, composite structures can also be formed with vastly different mechanical properties as compared to the individual networks. In this present paper, we present a constitutive model presented in a continuum framework aimed at capturing these effects. Special care is taken to formulate thermodynamically consistent evolution laws for dissipative effects. This model, incorporating possible anisotropic network properties, is based on a strain energy function, split into an isochoric and a volumetric part. Generalisation to three dimensions is performed by numerical integration over the unit sphere. Model predictions indicate that the constitutive model is well able to predict the elastic and viscoelastic response of biological networks, and to an extent also composite structures. Copyright © 2016 Elsevier Ltd. All rights reserved.
Bayesian latent feature modeling for modeling bipartite networks with overlapping groups
DEFF Research Database (Denmark)
Jørgensen, Philip H.; Mørup, Morten; Schmidt, Mikkel Nørgaard
2016-01-01
Bi-partite networks are commonly modelled using latent class or latent feature models. Whereas the existing latent class models admit marginalization of parameters specifying the strength of interaction between groups, existing latent feature models do not admit analytical marginalization...... by the notion of community structure such that the edge density within groups is higher than between groups. Our model further assumes that entities can have different propensities of generating links in one of the modes. The proposed framework is contrasted on both synthetic and real bi-partite networks...... feature representations in bipartite networks provides a new framework for accounting for structure in bi-partite networks using binary latent feature representations providing interpretable representations that well characterize structure as quantified by link prediction....
A Search Model with a Quasi-Network
DEFF Research Database (Denmark)
Ejarque, Joao Miguel
This paper adds a quasi-network to a search model of the labor market. Fitting the model to an average unemployment rate and to other moments in the data implies the presence of the network is not noticeable in the basic properties of the unemployment and job finding rates. However, the network...
A Combined Electro-Thermal Breakdown Model for Oil-Impregnated Paper
Directory of Open Access Journals (Sweden)
Meng Huang
2017-12-01
Full Text Available The breakdown property of oil-impregnated paper is a key factor for converter transformer design and operation, but it is not well understood. In this paper, breakdown voltages of oil-impregnated paper were measured at different temperatures. The results showed that with the increase of temperature, electrical, electro-thermal and thermal breakdown occurred successively. An electro-thermal breakdown model was proposed based on the heat equilibrium and space charge transport, and negative differential mobility was introduced to the model. It was shown that carrier mobility determined whether it was electrical or thermal breakdown, and the model can effectively explain the temperature-dependent breakdown.
Thermal expansion model for multiphase electronic packaging materials
International Nuclear Information System (INIS)
Allred, B.E.; Warren, W.E.
1991-01-01
Control of thermal expansion is often necessary in the design and selection of electronic packages. In some instances, it is desirable to have a coefficient of thermal expansion intermediate between values readily attainable with single or two phase materials. The addition of a third phase in the form of fillers, whiskers, or fibers can be used to attain intermediate expansions. To help design the thermal expansion of multiphase materials for specific applications, a closed form model has been developed that accurately predicts the effective elastic properties of isotropic filled materials and transversely isotropic lamina. Properties of filled matrix materials are used as inputs to the lamina model to obtain the composite elastic properties as a function of the volume fraction of each phase. Hybrid composites with two or more fiber types are easily handled with this model. This paper reports that results for glass, quartz, and Kevlar fibers with beta-eucryptite filled polymer matrices show good agreement with experimental results for X, Y, and Z thermal expansion coefficients
Energy Technology Data Exchange (ETDEWEB)
Bauer, Dan
2011-07-15
The thermal use of the underground for heating and cooling applications can be done with borehole heat exchangers. This work deals with the further development of the modelling of thermal transport processes inside and outside the borehole as well as with the application of the further developed models. The combination of high accuracy and short computation time is achieved by the development of three-dimensional thermal resistance and capacity models for borehole heat exchangers. Short transient transport processes can be calculated by the developed model with a considerable higher dynamic and accuracy than with known models from literature. The model is used to evaluate measurement data of a thermal response test by parameter estimation technique with a transient three-dimensional model for the first time. Clear advantages like shortening of the test duration are shown. The developed borehole heat exchanger model is combined with a three-dimensional description of the underground in the Finite-Element-Program FEFLOW. The influence of moving groundwater on borehole heat exchangers and borehole thermal energy stores is then quantified.
Thermal models pertaining to continental growth
International Nuclear Information System (INIS)
Morgan, P.; Ashwal, L.
1988-01-01
Thermal models are important to understanding continental growth as the genesis, stabilization, and possible recycling of continental crust are closely related to the tectonic processes of the earth which are driven primarily by heat. The thermal energy budget of the earth was slowly decreasing since core formation, and thus the energy driving the terrestrial tectonic engine was decreasing. This fundamental observation was used to develop a logic tree defining the options for continental growth throughout earth history
Richards, Lance
2014-01-01
The general aim of this work is to develop and demonstrate a prototype structural health monitoring system for thermal protection systems that incorporates piezoelectric acoustic emission (AE) sensors to detect the occurrence and location of damaging impacts, such as those from Micrometeoroid Orbital Debris (MMOD). The approach uses an optical fiber Bragg grating (FBG) sensor network to evaluate the effect of detected damage on the thermal conductivity of the TPS material. Following detection of an impact, the TPS would be exposed to a heat source, possibly the sun, and the temperature distribution on the inner surface in the vicinity of the impact measured by the FBG network. A similar procedure could also be carried out as a screening test immediately prior to re-entry. The implications of any detected anomalies in the measured temperature distribution will be evaluated for their significance in relation to the performance of the TPS during reentry. Such a robust TPS health monitoring system would ensure overall crew safety throughout the mission, especially during reentry.
Mathematical model for spreading dynamics of social network worms
International Nuclear Information System (INIS)
Sun, Xin; Liu, Yan-Heng; Han, Jia-Wei; Liu, Xue-Jie; Li, Bin; Li, Jin
2012-01-01
In this paper, a mathematical model for social network worm spreading is presented from the viewpoint of social engineering. This model consists of two submodels. Firstly, a human behavior model based on game theory is suggested for modeling and predicting the expected behaviors of a network user encountering malicious messages. The game situation models the actions of a user under the condition that the system may be infected at the time of opening a malicious message. Secondly, a social network accessing model is proposed to characterize the dynamics of network users, by which the number of online susceptible users can be determined at each time step. Several simulation experiments are carried out on artificial social networks. The results show that (1) the proposed mathematical model can well describe the spreading dynamics of social network worms; (2) weighted network topology greatly affects the spread of worms; (3) worms spread even faster on hybrid social networks
A comprehensive multi-local-world model for complex networks
International Nuclear Information System (INIS)
Fan Zhengping; Chen Guanrong; Zhang Yunong
2009-01-01
The nodes in a community within a network are much more connected to each other than to the others outside the community in the same network. This phenomenon has been commonly observed from many real-world networks, ranging from social to biological even to technical networks. Meanwhile, the number of communities in some real-world networks, such as the Internet and most social networks, are evolving with time. To model this kind of networks, the present Letter proposes a multi-local-world (MLW) model to capture and describe their essential topological properties. Based on the mean-field theory, the degree distribution of this model is obtained analytically, showing that the generated network has a novel topological feature as being not completely random nor completely scale-free but behaving somewhere between them. As a typical application, the MLW model is applied to characterize the Internet against some other models such as the BA, GBA, Fitness and HOT models, demonstrating the superiority of the new model.
Agent based modeling of energy networks
International Nuclear Information System (INIS)
Gonzalez de Durana, José María; Barambones, Oscar; Kremers, Enrique; Varga, Liz
2014-01-01
Highlights: • A new approach for energy network modeling is designed and tested. • The agent-based approach is general and no technology dependent. • The models can be easily extended. • The range of applications encompasses from small to large energy infrastructures. - Abstract: Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed
Numerical modeling of Thermal Response Tests in Energy Piles
Franco, A.; Toledo, M.; Moffat, R.; Herrera, P. A.
2013-05-01
Nowadays, thermal response tests (TRT) are used as the main tools for the evaluation of low enthalpy geothermal systems such as heat exchangers. The results of TRT are used for estimating thermal conductivity and thermal resistance values of those systems. We present results of synthetic TRT simulations that model the behavior observed in an experimental energy pile system, which was installed at the new building of the Faculty of Engineering of Universidad de Chile. Moreover, we also present a parametric study to identify the most influent parameters in the performance of this type of tests. The modeling was developed using the finite element software COMSOL Multiphysics, which allows the incorporation of flow and heat transport processes. The modeled system consists on a concrete pile with 1 m diameter and 28 m deep, which contains a 28 mm diameter PEX pipe arranged in a closed circuit. Three configurations were analyzed: a U pipe, a triple U and a helicoid shape implemented at the experimental site. All simulations were run considering transient response in a three-dimensional domain. The simulation results provided the temperature distribution on the pile for a set of different geometry and physical properties of the materials. These results were compared with analytical solutions which are commonly used to interpret TRT data. This analysis demonstrated that there are several parameters that affect the system response in a synthetic TRT. For example, the diameter of the simulated pile affects the estimated effective thermal conductivity of the system. Moreover, the simulation results show that the estimated thermal conductivity for a 1 m diameter pile did not stabilize even after 100 hours since the beginning of the test, when it reached a value 30% below value used to set up the material properties in the simulation. Furthermore, we observed different behaviors depending on the thermal properties of concrete and soil. According to the simulations, the thermal
Towards patient specific thermal modelling of the prostate
International Nuclear Information System (INIS)
Berg, Cornelis A T van den; Kamer, Jeroen B van de; Leeuw, Astrid A C ee; Jeukens, Cecile R L P N; Raaymakers, Bas W; Vulpen, Marco van; Lagendijk, Jan J W
2006-01-01
The application of thermal modelling for hyperthermia and thermal ablation is severely hampered by lack of information about perfusion and vasculature. However, recently, with the advent of sophisticated angiography and dynamic contrast enhanced (DCE) imaging techniques, it has become possible to image small vessels and blood perfusion bringing the ultimate goal of patient specific thermal modelling closer within reach. In this study dynamic contrast enhanced multi-slice CT imaging techniques are employed to investigate the feasibility of this concept for regional hyperthermia treatment of the prostate. The results are retrospectively compared with clinical thermometry data of a patient group from an earlier trial. Furthermore, the role of the prostate vasculature in the establishment of the prostate temperature distribution is studied. Quantitative 3D perfusion maps of the prostate were constructed for five patients using a distributed-parameter tracer kinetics model to analyse dynamic CT data. CT angiography was applied to construct a discrete vessel model of the pelvis. Additionally, a discrete vessel model of the prostate vasculature was constructed of a prostate taken from a human corpse. Three thermal modelling schemes with increasing inclusion of the patient specific physiological information were used to simulate the temperature distribution of the prostate during regional hyperthermia. Prostate perfusion was found to be heterogeneous and T3 prostate carcinomas are often characterized by a strongly elevated tumour perfusion (up to 70-80 ml 100 g -1 min -1 ). This elevated tumour perfusion leads to 1-2 deg. C lower tumour temperatures than thermal simulations based on a homogeneous prostate perfusion. Furthermore, the comparison has shown that the simulations with the measured perfusion maps result in consistently lower prostate temperatures than clinically achieved. The simulations with the discrete vessel model indicate that significant pre-heating takes
Infinite Multiple Membership Relational Modeling for Complex Networks
DEFF Research Database (Denmark)
Mørup, Morten; Schmidt, Mikkel Nørgaard; Hansen, Lars Kai
Learning latent structure in complex networks has become an important problem fueled by many types of networked data originating from practically all fields of science. In this paper, we propose a new non-parametric Bayesian multiplemembership latent feature model for networks. Contrary to existing...... multiplemembership models that scale quadratically in the number of vertices the proposedmodel scales linearly in the number of links admittingmultiple-membership analysis in large scale networks. We demonstrate a connection between the single membership relational model and multiple membership models and show...
Instantaneous thermal modeling of the DC-link capacitor in PhotoVoltaic systems
DEFF Research Database (Denmark)
Yang, Yongheng; Ma, Ke; Wang, Huai
2015-01-01
, instantaneous thermal modeling approaches considering mission profiles for the DC-link capacitor in single-phase PV systems are explored in this paper. These thermal modelling approaches are based on: a) fast Fourier transform, b) look-up tables, and c) ripple current reconstruction. Moreover, the thermal...... grid-connected PV system have been adopted to demonstrate a look-up table based modelling approach, where real-field daily ambient conditions are considered....... modelling approaches for the DC-link capacitors take into account the instantaneous thermal characteristics, which are more challenging to the capacitor reliability during operation. Such instantaneous thermal modeling approaches enable a translation of instantaneous capacitor power losses to capacitor...
Modeling Epidemics Spreading on Social Contact Networks.
Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua
2015-09-01
Social contact networks and the way people interact with each other are the key factors that impact on epidemics spreading. However, it is challenging to model the behavior of epidemics based on social contact networks due to their high dynamics. Traditional models such as susceptible-infected-recovered (SIR) model ignore the crowding or protection effect and thus has some unrealistic assumption. In this paper, we consider the crowding or protection effect and develop a novel model called improved SIR model. Then, we use both deterministic and stochastic models to characterize the dynamics of epidemics on social contact networks. The results from both simulations and real data set conclude that the epidemics are more likely to outbreak on social contact networks with higher average degree. We also present some potential immunization strategies, such as random set immunization, dominating set immunization, and high degree set immunization to further prove the conclusion.
Port Hamiltonian modeling of Power Networks
van Schaik, F.; van der Schaft, Abraham; Scherpen, Jacquelien M.A.; Zonetti, Daniele; Ortega, R
2012-01-01
In this talk a full nonlinear model for the power network in port–Hamiltonian framework is derived to study its stability properties. For this we use the modularity approach i.e., we first derive the models of individual components in power network as port-Hamiltonian systems and then we combine all
Graphical Model Theory for Wireless Sensor Networks
International Nuclear Information System (INIS)
Davis, William B.
2002-01-01
Information processing in sensor networks, with many small processors, demands a theory of computation that allows the minimization of processing effort, and the distribution of this effort throughout the network. Graphical model theory provides a probabilistic theory of computation that explicitly addresses complexity and decentralization for optimizing network computation. The junction tree algorithm, for decentralized inference on graphical probability models, can be instantiated in a variety of applications useful for wireless sensor networks, including: sensor validation and fusion; data compression and channel coding; expert systems, with decentralized data structures, and efficient local queries; pattern classification, and machine learning. Graphical models for these applications are sketched, and a model of dynamic sensor validation and fusion is presented in more depth, to illustrate the junction tree algorithm
A Simplified Network Model for Travel Time Reliability Analysis in a Road Network
Directory of Open Access Journals (Sweden)
Kenetsu Uchida
2017-01-01
Full Text Available This paper proposes a simplified network model which analyzes travel time reliability in a road network. A risk-averse driver is assumed in the simplified model. The risk-averse driver chooses a path by taking into account both a path travel time variance and a mean path travel time. The uncertainty addressed in this model is that of traffic flows (i.e., stochastic demand flows. In the simplified network model, the path travel time variance is not calculated by considering all travel time covariance between two links in the network. The path travel time variance is calculated by considering all travel time covariance between two adjacent links in the network. Numerical experiments are carried out to illustrate the applicability and validity of the proposed model. The experiments introduce the path choice behavior of a risk-neutral driver and several types of risk-averse drivers. It is shown that the mean link flows calculated by introducing the risk-neutral driver differ as a whole from those calculated by introducing several types of risk-averse drivers. It is also shown that the mean link flows calculated by the simplified network model are almost the same as the flows calculated by using the exact path travel time variance.
International Nuclear Information System (INIS)
Vaziri, N.; Erfani, A.; Monsefi, M.; Hajabri, A.
2008-01-01
In a reactor accident like loss of coolant accident , one or more signals may not be monitored by control panel for some reasons such as interruptions and so on. Therefore a fast alternative method could guarantee the safe and reliable exploration of nuclear power planets. In this study, we used artificial neural network with Elman recurrent structure to predict six thermal hydraulic signals in a loss of coolant accident after upper plenum break. In the prediction procedure, a few previous samples are fed to the artificial neural network and the output value or next time step is estimated by the network output. The Elman recurrent network is trained with the data obtained from the benchmark simulation of loss of coolant accident in VVER. The results reveal that the predicted values follow the real trends well and artificial neural network can be used as a fast alternative prediction tool in loss of coolant accident
FASTSAT-HSV01 Thermal Math Model Correlation
McKelvey, Callie
2011-01-01
This paper summarizes the thermal math model correlation effort for the Fast Affordable Science and Technology SATellite (FASTSAT-HSV01), which was designed, built and tested by NASA's Marshall Space Flight Center (MSFC) and multiple partners. The satellite launched in November 2010 on a Minotaur IV rocket from the Kodiak Launch Complex in Kodiak, Alaska. It carried three Earth science experiments and two technology demonstrations into a low Earth circular orbit with an inclination of 72deg and an altitude of 650 kilometers. The mission has been successful to date with science experiment activities still taking place daily. The thermal control system on this spacecraft was a passive design relying on thermo-optical properties and six heaters placed on specific components. Flight temperature data is being recorded every minute from the 48 Resistance Temperature Devices (RTDs) onboard the satellite structure and many of its avionics boxes. An effort has been made to correlate the thermal math model to the flight temperature data using Cullimore and Ring's Thermal Desktop and by obtaining Earth and Sun vector data from the Attitude Control System (ACS) team to create an "as-flown" orbit. Several model parameters were studied during this task to understand the spacecraft's sensitivity to these changes. Many "lessons learned" have been noted from this activity that will be directly applicable to future small satellite programs.
Development of thermal hydraulic models for the reliable regulatory auditing code
Energy Technology Data Exchange (ETDEWEB)
Chung, B. D.; Song, C. H.; Lee, Y. J.; Kwon, T. S. [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)
2003-04-15
The objective of this project is to develop thermal hydraulic models for use in improving the reliability of the regulatory auditing codes. The current year fall under the first step of the 3 year project, and the main researches were focused on identifying the candidate thermal hydraulic models for improvement and to develop prototypical model development. During the current year, the verification calculations submitted for the APR 1400 design certification have been reviewed, the experimental data from the MIDAS DVI experiment facility in KAERI have been analyzed and evaluated, candidate thermal hydraulic models for improvement have been identified, prototypical models for the improved thermal hydraulic models have been developed, items for experiment in connection with the model development have been identified, and preliminary design of the experiment has been carried out.
Development of thermal hydraulic models for the reliable regulatory auditing code
International Nuclear Information System (INIS)
Chung, B. D.; Song, C. H.; Lee, Y. J.; Kwon, T. S.
2003-04-01
The objective of this project is to develop thermal hydraulic models for use in improving the reliability of the regulatory auditing codes. The current year fall under the first step of the 3 year project, and the main researches were focused on identifying the candidate thermal hydraulic models for improvement and to develop prototypical model development. During the current year, the verification calculations submitted for the APR 1400 design certification have been reviewed, the experimental data from the MIDAS DVI experiment facility in KAERI have been analyzed and evaluated, candidate thermal hydraulic models for improvement have been identified, prototypical models for the improved thermal hydraulic models have been developed, items for experiment in connection with the model development have been identified, and preliminary design of the experiment has been carried out
Simplified Building Thermal Model Used for Optimal Control of Radiant Cooling System
Directory of Open Access Journals (Sweden)
Lei He
2016-01-01
Full Text Available MPC has the ability to optimize the system operation parameters for energy conservation. Recently, it has been used in HVAC systems for saving energy, but there are very few applications in radiant cooling systems. To implement MPC in buildings with radiant terminals, the predictions of cooling load and thermal environment are indispensable. In this paper, a simplified thermal model is proposed for predicting cooling load and thermal environment in buildings with radiant floor. In this thermal model, the black-box model is introduced to derive the incident solar radiation, while the genetic algorithm is utilized to identify the parameters of the thermal model. In order to further validate this simplified thermal model, simulated results from TRNSYS are compared with those from this model and the deviation is evaluated based on coefficient of variation of root mean square (CV. The results show that the simplified model can predict the operative temperature with a CV lower than 1% and predict cooling loads with a CV lower than 10%. For the purpose of supervisory control in HVAC systems, this simplified RC thermal model has an acceptable accuracy and can be used for further MPC in buildings with radiation terminals.
Thermal modeling of nickel-hydrogen battery cells operating under transient orbital conditions
Schrage, Dean S.
1991-01-01
An analytical study of the thermal operating characteristics of nickel-hydrogen battery cells is presented. Combined finite-element and finite-difference techniques are employed to arrive at a computationally efficient composite thermal model representing a series-cell arrangement operating in conjunction with a radiately coupled baseplate and coldplate thermal bus. An aggressive, low-mass design approach indicates that thermal considerations can and should direct the design of the thermal bus arrangement. Special consideration is given to the potential for mixed conductive and convective processes across the hydrogen gap. Results of a compressible flow model are presented and indicate the transfer process is suitably represented by molecular conduction. A high-fidelity thermal model of the cell stack (and related components) indicates the presence of axial and radial temperature gradients. A detailed model of the thermal bus reveals the thermal interaction of individual cells and is imperative for assessing the intercell temperature gradients.
Stochastic actor-oriented models for network change
Snijders, T.A.B.
1996-01-01
A class of models is proposed for longitudinal network data. These models are along the lines of methodological individualism: actors use heuristics to try to achieve their individual goals, subject to constraints. The current network structure is among these constraints. The models are continuous
International Nuclear Information System (INIS)
Vanneste, Johan; Bush, John A.; Hickenbottom, Kerri L.; Marks, Christopher A.; Jassby, David
2017-01-01
Development and selection of membranes for membrane distillation (MD) could be accelerated if all performance-determining characteristics of the membrane could be obtained during MD operation without the need to recur to specialized or cumbersome porosity or thermal conductivity measurement techniques. By redefining the thermal efficiency, the Schofield method could be adapted to describe the flux without prior knowledge of membrane porosity, thickness, or thermal conductivity. A total of 17 commercially available membranes were analyzed in terms of flux and thermal efficiency to assess their suitability for application in MD. The thermal-efficiency based model described the flux with an average %RMSE of 4.5%, which was in the same range as the standard deviation on the measured flux. The redefinition of the thermal efficiency also enabled MD to be used as a novel thermal conductivity measurement device for thin porous hydrophobic films that cannot be measured with the conventional laser flash diffusivity technique.
Aziz, Asim; Jamshed, Wasim; Aziz, Taha
2018-04-01
In the present research a simplified mathematical model for the solar thermal collectors is considered in the form of non-uniform unsteady stretching surface. The non-Newtonian Maxwell nanofluid model is utilized for the working fluid along with slip and convective boundary conditions and comprehensive analysis of entropy generation in the system is also observed. The effect of thermal radiation and variable thermal conductivity are also included in the present model. The mathematical formulation is carried out through a boundary layer approach and the numerical computations are carried out for Cu-water and TiO2-water nanofluids. Results are presented for the velocity, temperature and entropy generation profiles, skin friction coefficient and Nusselt number. The discussion is concluded on the effect of various governing parameters on the motion, temperature variation, entropy generation, velocity gradient and the rate of heat transfer at the boundary.
Hybrid neural network bushing model for vehicle dynamics simulation
International Nuclear Information System (INIS)
Sohn, Jeong Hyun; Lee, Seung Kyu; Yoo, Wan Suk
2008-01-01
Although the linear model was widely used for the bushing model in vehicle suspension systems, it could not express the nonlinear characteristics of bushing in terms of the amplitude and the frequency. An artificial neural network model was suggested to consider the hysteretic responses of bushings. This model, however, often diverges due to the uncertainties of the neural network under the unexpected excitation inputs. In this paper, a hybrid neural network bushing model combining linear and neural network is suggested. A linear model was employed to represent linear stiffness and damping effects, and the artificial neural network algorithm was adopted to take into account the hysteretic responses. A rubber test was performed to capture bushing characteristics, where sine excitation with different frequencies and amplitudes is applied. Random test results were used to update the weighting factors of the neural network model. It is proven that the proposed model has more robust characteristics than a simple neural network model under step excitation input. A full car simulation was carried out to verify the proposed bushing models. It was shown that the hybrid model results are almost identical to the linear model under several maneuvers
Thermal conductivity of the Lennard-Jones chain fluid model.
Galliero, Guillaume; Boned, Christian
2009-12-01
Nonequilibrium molecular dynamics simulations have been performed to estimate, analyze, and correlate the thermal conductivity of a fluid composed of short Lennard-Jones chains (up to 16 segments) over a large range of thermodynamic conditions. It is shown that the dilute gas contribution to the thermal conductivity decreases when the chain length increases for a given temperature. In dense states, simulation results indicate that the residual thermal conductivity of the monomer increases strongly with density, but is weakly dependent on the temperature. Compared to the monomer value, it has been noted that the residual thermal conductivity of the chain was slightly decreasing with its length. Using these results, an empirical relation, including a contribution due to the critical enhancement, is proposed to provide an accurate estimation of the thermal conductivity of the Lennard-Jones chain fluid model (up to 16 segments) over the domain 0.8values of the Lennard-Jones chain fluid model merge on the same "universal" curve when plotted as a function of the excess entropy. Furthermore, it is shown that the reduced configurational thermal conductivity of the Lennard-Jones chain fluid model is approximately proportional to the reduced excess entropy for all fluid states and all chain lengths.
Mathematical model of highways network optimization
Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.
2017-12-01
The article deals with the issue of highways network design. Studies show that the main requirement from road transport for the road network is to ensure the realization of all the transport links served by it, with the least possible cost. The goal of optimizing the network of highways is to increase the efficiency of transport. It is necessary to take into account a large number of factors that make it difficult to quantify and qualify their impact on the road network. In this paper, we propose building an optimal variant for locating the road network on the basis of a mathematical model. The article defines the criteria for optimality and objective functions that reflect the requirements for the road network. The most fully satisfying condition for optimality is the minimization of road and transport costs. We adopted this indicator as a criterion of optimality in the economic-mathematical model of a network of highways. Studies have shown that each offset point in the optimal binding road network is associated with all other corresponding points in the directions providing the least financial costs necessary to move passengers and cargo from this point to the other corresponding points. The article presents general principles for constructing an optimal network of roads.
Thermal modelling of a dry revolving vane compressor
Ooi, K. T.; Aw, K. T.
2017-08-01
The lubricant used in compressors serves to lubricate, to seal the gaps to reduce internal leakage and to a certain extent, to cool. However, a lubricant free compressor is attractive if lubricants become a source of contaminant, or in areas where the compressor needs be placed under any orientation, such as those in military or portable computing. In this paper, a thermal model for a dry revolving vane compressor is presented. This thermal model sets out to predict the steady-state operating temperatures of the compressor components. The lumped thermal conductance method was employed. The results of the components temperature will be presented and discussed. A high potential for overheating is observed at the shaft bearings.
Neural network modeling of associative memory: Beyond the Hopfield model
Dasgupta, Chandan
1992-07-01
A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying dynamics are used to store and associatively recall information, are described. In the first class of models, a hierarchical structure is used to store an exponentially large number of strongly correlated memories. The second class of models uses limit cycles to store and retrieve individual memories. A neurobiologically plausible network that generates low-amplitude periodic variations of activity, similar to the oscillations observed in electroencephalographic recordings, is also described. Results obtained from analytic and numerical studies of the properties of these networks are discussed.
Forty years of Fanger's model of thermal comfort: Comfort for all?
Hoof, van J.
2008-01-01
The predicted mean vote (PMV) model of thermal comfort, created by Fanger in the late 1960s, is used worldwide to assess thermal comfort. Fanger based his model on college-aged students for use in invariant environmental conditions in air-conditioned buildings in moderate thermal climate zones.
Geometric model for softwood transverse thermal conductivity. Part I
Hong-mei Gu; Audrey Zink-Sharp
2005-01-01
Thermal conductivity is a very important parameter in determining heat transfer rate and is required for developing of drying models and in industrial operations such as adhesive cure rate. Geometric models for predicting softwood thermal conductivity in the radial and tangential directions were generated in this study based on obervation and measurements of wood...
Sparsity in Model Gene Regulatory Networks
International Nuclear Information System (INIS)
Zagorski, M.
2011-01-01
We propose a gene regulatory network model which incorporates the microscopic interactions between genes and transcription factors. In particular the gene's expression level is determined by deterministic synchronous dynamics with contribution from excitatory interactions. We study the structure of networks that have a particular '' function '' and are subject to the natural selection pressure. The question of network robustness against point mutations is addressed, and we conclude that only a small part of connections defined as '' essential '' for cell's existence is fragile. Additionally, the obtained networks are sparse with narrow in-degree and broad out-degree, properties well known from experimental study of biological regulatory networks. Furthermore, during sampling procedure we observe that significantly different genotypes can emerge under mutation-selection balance. All the preceding features hold for the model parameters which lay in the experimentally relevant range. (author)
Alexandrov, Natalia (Technical Monitor); Kuby, Michael; Tierney, Sean; Roberts, Tyler; Upchurch, Christopher
2005-01-01
This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.
Zeng, Hao; Xie, Zhimin; Gu, Jianping; Sun, Huiyu
2018-03-01
A new thermomechanical network transition constitutive model is proposed in the study to describe the viscoelastic behavior of shape memory polymers (SMPs). Based on the microstructure of semi-crystalline SMPs, a new simplified transformation equation is proposed to describe the transform of transient networks. And the generalized fractional Maxwell model is introduced in the paper to estimate the temperature-dependent storage modulus. In addition, a neo-KAHR theory with multiple discrete relaxation processes is put forward to study the structural relaxation of the nonlinear thermal strain in cooling/heating processes. The evolution equations of the time- and temperature-dependent stress and strain response are developed. In the model, the thermodynamical and mechanical characteristics of SMPs in the typical thermomechanical cycle are described clearly and the irreversible deformation is studied in detail. Finally, the typical thermomechanical cycles are simulated using the present constitutive model, and the simulation results agree well with the experimental results.
Measurement and model on thermal properties of sintered diamond composites
International Nuclear Information System (INIS)
Moussa, Tala; Garnier, Bertrand; Peerhossaini, Hassan
2013-01-01
Highlights: ► Thermal properties of sintered diamond used for grinding is studied. ► Flash method with infrared temperature measurement is used to investigate. ► Thermal conductivity increases with the amount of diamond. ► It is very sensitive to binder conductivity. ► Results agree with models assuming imperfect contact between matrix and particles. - Abstract: A prelude to the thermal management of grinding processes is measurement of the thermal properties of working materials. Indeed, tool materials must be chosen not only for their mechanical properties (abrasion performance, lifetime…) but also for thermal concerns (thermal conductivity) for efficient cooling that avoids excessive temperatures in the tool and workpiece. Sintered diamond is currently used for grinding tools since it yields higher performances and longer lifetimes than conventional materials (mineral or silicon carbide abrasives), but its thermal properties are not yet well known. Here the thermal conductivity, heat capacity and density of sintered diamond are measured as functions of the diamond content in composites and for two types of metallic binders: hard tungsten-based and soft cobalt-based binders. The measurement technique for thermal conductivity is derived from the flash method. After pulse heating, the temperature of the rear of the sample is measured with a noncontact method (infrared camera). A parameter estimation method associated with a three-layer nonstationary thermal model is used to obtain sample thermal conductivity, heat transfer coefficient and absorbed energy. With the hard metallic binder, the thermal conductivity of sintered diamond increased by up to 64% for a diamond content increasing from 0 to 25%. The increase is much less for the soft binder: 35% for diamond volumes up to 25%. In addition, experimental data were found that were far below the value predicted by conventional analytical models for effective thermal conductivity. A possible explanation
Modeling the thermal absorption factor of photovoltaic/thermal combi-panels
International Nuclear Information System (INIS)
Santbergen, R.; Zolingen, R.J.Ch. van
2006-01-01
In a photovoltaic/thermal combi-panel solar cells generate electricity while residual heat is extracted to be used for tap water heating or room heating. In such a panel the entire solar spectrum can be used in principle. Unfortunately long wavelength solar irradiance is poorly absorbed by the semiconductor material in standard solar cells. A computer model was developed to determine the thermal absorption factor of crystalline silicon solar cells. It was found that for a standard untextured solar cell with a silver back contact a relatively large amount of long wavelength irradiance is lost by reflection resulting in an absorption factor of only 74%. The model was then used to investigate ways to increase this absorption factor. One way is absorbing long wavelength irradiance in a second absorber behind a semi-transparent solar cell. According to the model this will increase the total absorption factor to 87%. The second way is to absorb irradiance in the back contact of the solar cell by using rough interfaces in combination with a non-standard metal as back contact. Theoretically the absorption factor can then be increased to 85%
Thermal-Hydraulic Experiments and Modelling for Advanced Nuclear Reactor Systems
International Nuclear Information System (INIS)
Song, C. H.; Chung, M. K.; Park, C. K. and others
2005-04-01
The objectives of the project are to study thermal hydraulic characteristics of reactor primary system for the verification of the reactor safety and to evaluate new safety concepts of new safety design features. To meet the research goal, several thermal hydraulic experiments were performed and related thermal hydraulic models were developed with the experimental data which were produced through the thermal hydraulic experiments. Followings are main research topics; - Multi-dimensional Phenomena in a Reactor Vessel Downcomer - Condensation Load and Thermal Mixing in the IRWST - Development of Thermal-Hydraulic Models for Two-Phase Flow - Development of Measurement Techniques for Two-Phase Flow - Supercritical Reactor T/H Characteristics Analysis From the above experimental and analytical studies, new safety design features of the advanced power reactors were verified and lots of the safety issues were also resolved
Thermal-Hydraulic Experiments and Modelling for Advanced Nuclear Reactor Systems
Energy Technology Data Exchange (ETDEWEB)
Song, C. H.; Chung, M. K.; Park, C. K. and others
2005-04-15
The objectives of the project are to study thermal hydraulic characteristics of reactor primary system for the verification of the reactor safety and to evaluate new safety concepts of new safety design features. To meet the research goal, several thermal hydraulic experiments were performed and related thermal hydraulic models were developed with the experimental data which were produced through the thermal hydraulic experiments. Followings are main research topics; - Multi-dimensional Phenomena in a Reactor Vessel Downcomer - Condensation Load and Thermal Mixing in the IRWST - Development of Thermal-Hydraulic Models for Two-Phase Flow - Development of Measurement Techniques for Two-Phase Flow - Supercritical Reactor T/H Characteristics Analysis From the above experimental and analytical studies, new safety design features of the advanced power reactors were verified and lots of the safety issues were also resolved.
Modeling of High Temperature Oxidation Behavior of FeCrAl Alloy by using Artificial Neural Network
Energy Technology Data Exchange (ETDEWEB)
Kim, Jae Joon; Ryu, Ho Jin [KAIST, Daejeon (Korea, Republic of)
2016-10-15
Refractory alloys are candidate materials for replacing current zirconium-base cladding of light water reactors and they retain significant creep resistance and mechanical strength at high temperatures up to 1500 ℃ due to their high melting temperature. Thermal neutron cross sections of refractory metals are higher than that of zirconium, however the loss of neutron can be overcome by reducing cladding thickness which can be facilitated with enhanced mechanical properties. However, most refractory metals show the poor oxidation resistance at a high temperature. Oxidation behaviors of the various compositions of FeCrAl alloys in high temperature conditions were modeled by using Bayesian neural network. The automatic relevance determination (ARD) technique represented the influence of the composition of alloying elements on the oxidation resistance of FeCrAl alloys. This model can be utilized to understand the tendency of oxidation behavior along the composition of each element and prove the applicability of neural network modeling for the development of new cladding material of light water reactors.
Final report of the 'Nordic thermal-hydraulic and safety network (NOTNET)' - Project
Energy Technology Data Exchange (ETDEWEB)
Tuunanen, J.; Tuomainen, M. [VTT Processes (Finland)
2005-04-01
A Nordic network for thermal-hydraulics and nuclear safety research was started. The idea of the network is to combine the resources of different research teams in order to carry out more ambitious and extensive research programs than would be possible for the individual teams. From the very beginning, the end users of the research results have been integrated to the network. Aim of the network is to benefit the partners involved in nuclear energy in the Nordic Countries (power companies, reactor vendors, safety regulators, research units). First task within the project was to describe the resources (personnel, know-how, simulation tools, test facilities) of the various teams. Next step was to discuss with the end users about their research needs. Based on these steps, few most important research topics with defined goals were selected, and coarse road maps were prepared for reaching the targets. These road maps will be used as a starting point for planning the actual research projects in the future. The organisation and work plan for the network were established. National coordinators were appointed, as well as contact persons in each participating organisation, whether research unit or end user. This organisation scheme is valid for the short-term operation of NOTNET when only Nordic organisations take part in the work. Later on, it is possible to enlarge the network e.g. within EC framework programme. The network can now start preparing project proposals and searching funding for the first common research projects. (au)
International Nuclear Information System (INIS)
Zainazlan Md Zain; Mohd Nasir Taib; Shahrizam Mohd Shah Baki
2006-01-01
Strategies to improve energy efficiency in buildings have continuously being improved and becoming more effective as new knowledge on the building behavior and technology continue to develop. Nevertheless, effort to explore for further improvement must continuously undertake to seek more energy efficient and cost effective systems. Artificial Neural Network (ANN) is currently one of the most popular mechanisms to forecast any form of behavior and phenomena. Building thermal behavior can be studied and potential for energy utilization improvement without compromising thermal comfort can be explored using ANN. This paper explores the possibility of monitoring, predicting and forecasting the thermal behavior inside a building space and the optimization of building design. Typical result of experimental data and simulated data is presented. The sample house used adopted various thermal comfort strategies like cross ventilation and space air flow consideration
Optimal transportation networks models and theory
Bernot, Marc; Morel, Jean-Michel
2009-01-01
The transportation problem can be formalized as the problem of finding the optimal way to transport a given measure into another with the same mass. In contrast to the Monge-Kantorovitch problem, recent approaches model the branched structure of such supply networks as minima of an energy functional whose essential feature is to favour wide roads. Such a branched structure is observable in ground transportation networks, in draining and irrigation systems, in electrical power supply systems and in natural counterparts such as blood vessels or the branches of trees. These lectures provide mathematical proof of several existence, structure and regularity properties empirically observed in transportation networks. The link with previous discrete physical models of irrigation and erosion models in geomorphology and with discrete telecommunication and transportation models is discussed. It will be mathematically proven that the majority fit in the simple model sketched in this volume.
DEFF Research Database (Denmark)
Sindbæk, Søren Michael
2015-01-01
preserve patterns of thisinteraction. Formal network analysis and modelling holds the potential to identify anddemonstrate such patterns, where traditional methods often prove inadequate. Thearchaeological study of communication networks in the past, however, calls for radically different analytical...... this is not a problem of network analysis, but network synthesis: theclassic problem of cracking codes or reconstructing black-box circuits. It is proposedthat archaeological approaches to network synthesis must involve a contextualreading of network data: observations arising from individual contexts, morphologies...
Road network safety evaluation using Bayesian hierarchical joint model.
Wang, Jie; Huang, Helai
2016-05-01
Safety and efficiency are commonly regarded as two significant performance indicators of transportation systems. In practice, road network planning has focused on road capacity and transport efficiency whereas the safety level of a road network has received little attention in the planning stage. This study develops a Bayesian hierarchical joint model for road network safety evaluation to help planners take traffic safety into account when planning a road network. The proposed model establishes relationships between road network risk and micro-level variables related to road entities and traffic volume, as well as socioeconomic, trip generation and network density variables at macro level which are generally used for long term transportation plans. In addition, network spatial correlation between intersections and their connected road segments is also considered in the model. A road network is elaborately selected in order to compare the proposed hierarchical joint model with a previous joint model and a negative binomial model. According to the results of the model comparison, the hierarchical joint model outperforms the joint model and negative binomial model in terms of the goodness-of-fit and predictive performance, which indicates the reasonableness of considering the hierarchical data structure in crash prediction and analysis. Moreover, both random effects at the TAZ level and the spatial correlation between intersections and their adjacent segments are found to be significant, supporting the employment of the hierarchical joint model as an alternative in road-network-level safety modeling as well. Copyright © 2016 Elsevier Ltd. All rights reserved.
Modeling online social networks based on preferential linking
International Nuclear Information System (INIS)
Hu Hai-Bo; Chen Jun; Guo Jin-Li
2012-01-01
We study the phenomena of preferential linking in a large-scale evolving online social network and find that the linear preference holds for preferential creation, preferential acceptance, and preferential attachment. Based on the linear preference, we propose an analyzable model, which illustrates the mechanism of network growth and reproduces the process of network evolution. Our simulations demonstrate that the degree distribution of the network produced by the model is in good agreement with that of the real network. This work provides a possible bridge between the micro-mechanisms of network growth and the macrostructures of online social networks
Stabilization of model-based networked control systems
Energy Technology Data Exchange (ETDEWEB)
Miranda, Francisco [CIDMA, Universidade de Aveiro, Aveiro (Portugal); Instituto Politécnico de Viana do Castelo, Viana do Castelo (Portugal); Abreu, Carlos [Instituto Politécnico de Viana do Castelo, Viana do Castelo (Portugal); CMEMS-UMINHO, Universidade do Minho, Braga (Portugal); Mendes, Paulo M. [CMEMS-UMINHO, Universidade do Minho, Braga (Portugal)
2016-06-08
A class of networked control systems called Model-Based Networked Control Systems (MB-NCSs) is considered. Stabilization of MB-NCSs is studied using feedback controls and simulation of stabilization for different feedbacks is made with the purpose to reduce the network trafic. The feedback control input is applied in a compensated model of the plant that approximates the plant dynamics and stabilizes the plant even under slow network conditions. Conditions for global exponential stabilizability and for the choosing of a feedback control input for a given constant time between the information moments of the network are derived. An optimal control problem to obtain an optimal feedback control is also presented.
Hall Thruster Thermal Modeling and Test Data Correlation
Myers, James; Kamhawi, Hani; Yim, John; Clayman, Lauren
2016-01-01
The life of Hall Effect thrusters are primarily limited by plasma erosion and thermal related failures. NASA Glenn Research Center (GRC) in cooperation with the Jet Propulsion Laboratory (JPL) have recently completed development of a Hall thruster with specific emphasis to mitigate these limitations. Extending the operational life of Hall thursters makes them more suitable for some of NASA's longer duration interplanetary missions. This paper documents the thermal model development, refinement and correlation of results with thruster test data. Correlation was achieved by minimizing uncertainties in model input and recognizing the relevant parameters for effective model tuning. Throughout the thruster design phase the model was used to evaluate design options and systematically reduce component temperatures. Hall thrusters are inherently complex assemblies of high temperature components relying on internal conduction and external radiation for heat dispersion and rejection. System solutions are necessary in most cases to fully assess the benefits and/or consequences of any potential design change. Thermal model correlation is critical since thruster operational parameters can push some components/materials beyond their temperature limits. This thruster incorporates a state-of-the-art magnetic shielding system to reduce plasma erosion and to a lesser extend power/heat deposition. Additionally a comprehensive thermal design strategy was employed to reduce temperatures of critical thruster components (primarily the magnet coils and the discharge channel). Long term wear testing is currently underway to assess the effectiveness of these systems and consequently thruster longevity.
Discrete dynamic modeling of cellular signaling networks.
Albert, Réka; Wang, Rui-Sheng
2009-01-01
Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.
Neural network tagging in a toy model
International Nuclear Information System (INIS)
Milek, Marko; Patel, Popat
1999-01-01
The purpose of this study is a comparison of Artificial Neural Network approach to HEP analysis against the traditional methods. A toy model used in this analysis consists of two types of particles defined by four generic properties. A number of 'events' was created according to the model using standard Monte Carlo techniques. Several fully connected, feed forward multi layered Artificial Neural Networks were trained to tag the model events. The performance of each network was compared to the standard analysis mechanisms and significant improvement was observed
Thermal modelling. Preliminary site description. Forsmark area - version 1.2
Energy Technology Data Exchange (ETDEWEB)
Sundberg, Jan; Back, Paer-Erik; Bengtsson, Anna; Laendell, Maerta [Geo Innova AB, Linkoeping (Sweden)
2005-08-01
This report presents the thermal site descriptive model for the Forsmark area, version 1.2. The main objective of this report is to present the thermal modelling work where data has been identified, quality controlled, evaluated and summarised in order to make an upscaling to lithological domain level possible. The thermal conductivity at canister scale has been modelled for two different lithological domains (RFM029 and RFM012, both dominated by granite to granodiorite (101057)). A main modelling approach has been used to determine the mean value of the thermal conductivity. Two alternative/complementary approaches have been used to evaluate the spatial variability of the thermal conductivity at domain level. The thermal modelling approaches are based on the lithological model for the Forsmark area, version 1.2 together with rock type models constituted from measured and calculated (from mineral composition) thermal conductivities. Results indicate that the mean of thermal conductivity is expected to exhibit a small variation between the different domains, 3.46 W/(mxK) for RFM012 to 3.55 W/(mxK) for RFM029. The spatial distribution of the thermal conductivity does not follow a simple model. Lower and upper 95% confidence limits are based on the modelling results, but have been rounded of to only two significant figures. Consequently, the lower limit is 2.9 W/(mxK), while the upper is 3.8 W/(mxK). This is applicable to both the investigated domains. The temperature dependence is rather small with a decrease in thermal conductivity of 10.0% per 100 deg C increase in temperature for the dominating rock type. There are a number of important uncertainties associated with these results. One of the uncertainties considers the representative scale for the canister. Another important uncertainty is the methodological uncertainties associated with the upscaling of thermal conductivity from cm-scale to canister scale. In addition, the representativeness of rock samples is
Frequency-domain thermal modelling of power semiconductor devices
DEFF Research Database (Denmark)
Ma, Ke; Blaabjerg, Frede; Andresen, Markus
2015-01-01
to correctly predict the device temperatures, especially when considering the thermal grease and heat sink attached to the power semiconductor devices. In this paper, the frequency-domain approach is applied to the modelling of thermal dynamics for power devices. The limits of the existing RC lump...
Thermal modelling of a torpedo-car
International Nuclear Information System (INIS)
Verdeja-Gonzalez, L. F.; Barbes-Fernandez, M. F.; Gonzalez-Ojeda, R.; Castillo, G. A.; Colas, R.
2005-01-01
A two-dimensional finite element model for computing the temperature distribution in a torpedo-car holding pig iron is described in this work. The model determines the temperature gradients in steady and transient conditions whiting the different parts that constitute the systems, which are considered to be the steel casing, refractory lining, liquid iron, slag and air. Heat transfer within the main fluid phases (iron and air) is computed assuming an apparent thermal conductivity term incorporating the contribution from convention and radiation, and it is affected by the dimensions of the vessel. Thermal gradients within the constituents of the torpedo-car are used to calculate heat losses during operation. It was found that the model required the incorporate of a region within the iron-refractory interface to reproduce thermographic data recorded during operation; the heat transfer coefficient of this interface was found to be equal to 30 Wm''-2K''-1. (Author) 11 refs
Thermal modelling of a torpedo-car
Energy Technology Data Exchange (ETDEWEB)
Verdeja-Gonzalez, L. F.; Barbes-Fernandez, M. F.; Gonzalez-Ojeda, R.; Castillo, G. A.; Colas, R.
2005-07-01
A two-dimensional finite element model for computing the temperature distribution in a torpedo-car holding pig iron is described in this work. The model determines the temperature gradients in steady and transient conditions whiting the different parts that constitute the systems, which are considered to be the steel casing, refractory lining, liquid iron, slag and air. Heat transfer within the main fluid phases (iron and air) is computed assuming an apparent thermal conductivity term incorporating the contribution from convention and radiation, and it is affected by the dimensions of the vessel. Thermal gradients within the constituents of the torpedo-car are used to calculate heat losses during operation. It was found that the model required the incorporate of a region within the iron-refractory interface to reproduce thermographic data recorded during operation; the heat transfer coefficient of this interface was found to be equal to 30 Wm''-2K''-1. (Author) 11 refs.
Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model
Energy Technology Data Exchange (ETDEWEB)
Rossi, R; Gallagher, B; Neville, J; Henderson, K
2011-11-11
Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied our model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.
Modelling characteristics of photovoltaic panels with thermal phenomena taken into account
International Nuclear Information System (INIS)
Krac, Ewa; Górecki, Krzysztof
2016-01-01
In the paper a new form of the electrothermal model of photovoltaic panels is proposed. This model takes into account the optical, electrical and thermal properties of the considered panels, as well as electrical and thermal properties of the protecting circuit and thermal inertia of the considered panels. The form of this model is described and some results of measurements and calculations of mono-crystalline and poly-crystalline panels are presented
DEFF Research Database (Denmark)
Tunzi, Michele; Boukhanouf, Rabah; Li, Hongwei
2018-01-01
This paper presents results of a research study into improving energy performance of small-scale district heat network through water supply and return temperature optimization technique. The case study involves establishing the baseline heat demand of the estate’s buildings, benchmarking...... the existing heat network operating parameters, and defining the optimum supply and return temperature. A stepwise temperature optimization technique of plate radiators heat emitters was applied to control the buildings indoor thermal comfort using night set back temperature strategy of 21/18 °C....... It was established that the heat network return temperature could be lowered from the current measured average of 55 °C to 35.6 °C, resulting in overall reduction of heat distribution losses and fuel consumption of 10% and 9% respectively. Hence, the study demonstrates the potential of operating existing heat...
Thermal margin comparison between DAM and simple model
Energy Technology Data Exchange (ETDEWEB)
Cha, Jeonghun; Yook, Daesik [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)
2017-01-15
The nuclear industry in Korea, has considered using a detail analysis model (DAM), which described each rod, to get more thermal margin with the design a dry storage facility for nuclear spent fuel (NSF). A DAM is proposed and a thermal analysis to determine the cladding integrity is performed using test conditions with a homogenized NSF assembly analysis model(Simple model). The result show that according to USA safety criteria, temperature of canister surface has to keep below 500 K in normal condition and 630 K in excess condition. A commercial Computational Fluid Dynamics (CFD) called ANSYS Fluent version 14.5 was used.
International Nuclear Information System (INIS)
Mehta, Siddharth; Chauhan, K. Prashanth; Kanagaraj, S.
2011-01-01
Nanofluid is an innovative heat transfer fluid with superior potential for enhancing the heat transfer performance of conventional fluids. Though many attempts have been made to investigate the abnormal high thermal conductivity of nanofluids, the existing models cannot precisely predict the same. An attempt has been made to develop a model for predicting the thermal conductivity of different types of nanofluids. The model presented here is derived based on the fact that thermal conductivity of nanofluids depends on thermal conductivity of particle and fluid as well as micro-convective heat transfer due to Brownian motion of nanoparticles. Novelty of the article lies in giving a unique equation which predicts thermal conductivity of nanofluids for different concentrations and particle sizes which also correctly predicts the trends observed in experimental data over a wide range of particle sizes, temperatures, and particle concentrations.
Guo, Guifang; Long, Bo; Cheng, Bo; Zhou, Shiqiong; Xu, Peng; Cao, Binggang
In order to better understand the thermal abuse behavior of high capacities and large power lithium-ion batteries for electric vehicle application, a three-dimensional thermal model has been developed for analyzing the temperature distribution under abuse conditions. The model takes into account the effects of heat generation, internal conduction and convection, and external heat dissipation to predict the temperature distribution in a battery. Three-dimensional model also considers the geometrical features to simulate oven test, which are significant in larger cells for electric vehicle application. The model predictions are compared to oven test results for VLP 50/62/100S-Fe (3.2 V/55 Ah) LiFePO 4/graphite cells and shown to be in great agreement.
VHTR core modeling: coupling between neutronic and thermal-hydraulics
International Nuclear Information System (INIS)
Limaiem, I.; Damian, F.; Raepsaet, X.; Studer, E.
2005-01-01
Following the present interest in the next generation nuclear power plan (NGNP), Cea is deploying special effort to develop new models and qualify its research tools for this next generation reactors core. In this framework, the Very High Temperature Reactor concept (VHTR) has an increasing place in the actual research program. In such type of core, a strong interaction exists between neutronic and thermal-hydraulics. Consequently, the global core modelling requires accounting for the temperature feedback in the neutronic models. The purpose of this paper is to present the new neutronic and thermal-hydraulics coupling model dedicated to the High Temperature Reactors (HTR). The coupling model integrates a new version of the neutronic scheme calculation developed in collaboration between Cea and Framatome-ANP. The neutronic calculations are performed using a specific calculation processes based on the APOLLO2 transport code and CRONOS2 diffusion code which are part of the French reactor physics code system SAPHYR. The thermal-hydraulics model is characterised by an equivalent porous media and 1-D fluid/3-D thermal model implemented in the CAST3M/ARCTURUS code. The porous media approach involves the definition of both homogenous and heterogeneous models to ensure a correct temperature feedback. This study highlights the sensitivity of the coupling system's parameters (radial/axial meshing and data exchange strategy between neutronic and thermal-hydraulics code). The parameters sensitivity study leads to the definition of an optimal coupling system specification for the VHTR. Besides, this work presents the first physical analysis of the VHTR core in steady-state condition. The analysis gives information about the 3-D power peaking and the temperature coefficient. Indeed, it covers different core configurations with different helium distribution in the core bypass. (authors)
Improved Maximum Parsimony Models for Phylogenetic Networks.
Van Iersel, Leo; Jones, Mark; Scornavacca, Celine
2018-05-01
Phylogenetic networks are well suited to represent evolutionary histories comprising reticulate evolution. Several methods aiming at reconstructing explicit phylogenetic networks have been developed in the last two decades. In this article, we propose a new definition of maximum parsimony for phylogenetic networks that permits to model biological scenarios that cannot be modeled by the definitions currently present in the literature (namely, the "hardwired" and "softwired" parsimony). Building on this new definition, we provide several algorithmic results that lay the foundations for new parsimony-based methods for phylogenetic network reconstruction.
Thermal conductivity model for powdered materials under vacuum based on experimental studies
Directory of Open Access Journals (Sweden)
N. Sakatani
2017-01-01
Full Text Available The thermal conductivity of powdered media is characteristically very low in vacuum, and is effectively dependent on many parameters of their constituent particles and packing structure. Understanding of the heat transfer mechanism within powder layers in vacuum and theoretical modeling of their thermal conductivity are of great importance for several scientific and engineering problems. In this paper, we report the results of systematic thermal conductivity measurements of powdered media of varied particle size, porosity, and temperature under vacuum using glass beads as a model material. Based on the obtained experimental data, we investigated the heat transfer mechanism in powdered media in detail, and constructed a new theoretical thermal conductivity model for the vacuum condition. This model enables an absolute thermal conductivity to be calculated for a powder with the input of a set of powder parameters including particle size, porosity, temperature, and compressional stress or gravity, and vice versa. Our model is expected to be a competent tool for several scientific and engineering fields of study related to powders, such as the thermal infrared observation of air-less planetary bodies, thermal evolution of planetesimals, and performance of thermal insulators and heat storage powders.
Toward Improved Fidelity of Thermal Explosion Simulations
Energy Technology Data Exchange (ETDEWEB)
Nichols, A L; Becker, R; Howard, W M; Wemhoff, A
2009-07-17
We will present results of an effort to improve the thermal/chemical/mechanical modeling of HMX based explosive like LX04 and LX10 for thermal cook-off. The original HMX model and analysis scheme were developed by Yoh et.al. for use in the ALE3D modeling framework. The current results were built to remedy the deficiencies of that original model. We concentrated our efforts in four areas. The first area was addition of porosity to the chemical material model framework in ALE3D that is used to model the HMX explosive formulation. This is needed to handle the roughly 2% porosity in solid explosives. The second area was the improvement of the HMX reaction network, which included the inclusion of a reactive phase change model base on work by Henson et.al. The third area required adding early decomposition gas species to the CHEETAH material database to develop more accurate equations of state for gaseous intermediates and products. Finally, it was necessary to improve the implicit mechanics module in ALE3D to more naturally handle the long time scales associated with thermal cook-off. The application of the resulting framework to the analysis of the Scaled Thermal Explosion (STEX) experiments will be discussed.
Thermal and mechanical modelling of a mig-type electron gun
International Nuclear Information System (INIS)
Patire Junior, H.; Castro, J.J.B. de
1995-01-01
A thermal and mechanical modelling of a magnetron injection electron gun has been made to minimize the temperature distribution in the gun elements while keeping the required operating temperature at 1000 0 C of the emitter. Appropriate materials were selected to reduce thermal losses and to improve the gun design from a constructional point of view aiming at extending the capabilities of the gun. A software has been used to simulate a thermal model considering the three processes of thermal transfer and the influence of the physical properties of the materials used. (author). 8 refs., 2 figs, 2 tabs
Directory of Open Access Journals (Sweden)
Xiangyang Liu
2018-03-01
Full Text Available An appropriate model to correct thermal radiation anisotropy is important for the wide applications of land surface temperature (LST. This paper evaluated the performance of three published directional thermal radiation models—the Roujean–Lagouarde (RL model, the Bidirectional Reflectance Distribution Function (BRDF model, and the Vinnikov model—at canopy and pixel scale using simulation, airborne, and satellite data. The results at canopy scale showed that (1 the three models could describe directional anisotropy well and the Vinnikov model performed the best, especially for erectophile canopy or low leaf area index (LAI; (2 the three models reached the highest fitting accuracy when the LAI varied from 1 to 2; and (3 the capabilities of the three models were all restricted by the hotspot effect, plant height, plant spacing, and three-dimensional structure. The analysis at pixel scale indicated a consistent result that the three models presented a stable effect both on verification and validation, but the Vinnikov model had the best ability in the erectophile canopy (savannas and grassland and low LAI (barren or sparsely vegetated areas. Therefore, the Vinnikov model was calibrated for different land cover types to instruct the angular correction of LST. Validation with the Surface Radiation Budget Network (SURFRAD-measured LST demonstrated that the root mean square (RMSE of the Moderate Resolution Imaging Spectroradiometer (MODIS LST product could be decreased by 0.89 K after angular correction. In addition, the corrected LST showed better spatial uniformity and higher angular correlation.
Equity venture capital platform model based on complex network
Guo, Dongwei; Zhang, Lanshu; Liu, Miao
2018-05-01
This paper uses the small-world network and the random-network to simulate the relationship among the investors, construct the network model of the equity venture capital platform to explore the impact of the fraud rate and the bankruptcy rate on the robustness of the network model while observing the impact of the average path length and the average agglomeration coefficient of the investor relationship network on the income of the network model. The study found that the fraud rate and bankruptcy rate exceeded a certain threshold will lead to network collapse; The bankruptcy rate has a great influence on the income of the platform; The risk premium exists, and the average return is better under a certain range of bankruptcy risk; The structure of the investor relationship network has no effect on the income of the investment model.
Resolving structural variability in network models and the brain.
Directory of Open Access Journals (Sweden)
Florian Klimm
2014-03-01
Full Text Available Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling--in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity do not in general simultaneously display a second (e.g., hierarchy. This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful
A Network Contention Model for the Extreme-scale Simulator
Energy Technology Data Exchange (ETDEWEB)
Engelmann, Christian [ORNL; Naughton III, Thomas J [ORNL
2015-01-01
The Extreme-scale Simulator (xSim) is a performance investigation toolkit for high-performance computing (HPC) hardware/software co-design. It permits running a HPC application with millions of concurrent execution threads, while observing its performance in a simulated extreme-scale system. This paper details a newly developed network modeling feature for xSim, eliminating the shortcomings of the existing network modeling capabilities. The approach takes a different path for implementing network contention and bandwidth capacity modeling using a less synchronous and accurate enough model design. With the new network modeling feature, xSim is able to simulate on-chip and on-node networks with reasonable accuracy and overheads.
Innovative research of AD HOC network mobility model
Chen, Xin
2017-08-01
It is difficult for researchers of AD HOC network to conduct actual deployment during experimental stage as the network topology is changeable and location of nodes is unfixed. Thus simulation still remains the main research method of the network. Mobility model is an important component of AD HOC network simulation. It is used to describe the movement pattern of nodes in AD HOC network (including location and velocity, etc.) and decides the movement trail of nodes, playing as the abstraction of the movement modes of nodes. Therefore, mobility model which simulates node movement is an important foundation for simulation research. In AD HOC network research, mobility model shall reflect the movement law of nodes as truly as possible. In this paper, node generally refers to the wireless equipment people carry. The main research contents include how nodes avoid obstacles during movement process and the impacts of obstacles on the mutual relation among nodes, based on which a Node Self Avoiding Obstacle, i.e. NASO model is established in AD HOC network.
Stochastic modeling of thermal fatigue crack growth
Radu, Vasile
2015-01-01
The book describes a systematic stochastic modeling approach for assessing thermal-fatigue crack-growth in mixing tees, based on the power spectral density of temperature fluctuation at the inner pipe surface. It shows the development of a frequency-temperature response function in the framework of single-input, single-output (SISO) methodology from random noise/signal theory under sinusoidal input. The frequency response of stress intensity factor (SIF) is obtained by a polynomial fitting procedure of thermal stress profiles at various instants of time. The method, which takes into account the variability of material properties, and has been implemented in a real-world application, estimates the probabilities of failure by considering a limit state function and Monte Carlo analysis, which are based on the proposed stochastic model. Written in a comprehensive and accessible style, this book presents a new and effective method for assessing thermal fatigue crack, and it is intended as a concise and practice-or...
Building functional networks of spiking model neurons.
Abbott, L F; DePasquale, Brian; Memmesheimer, Raoul-Martin
2016-03-01
Most of the networks used by computer scientists and many of those studied by modelers in neuroscience represent unit activities as continuous variables. Neurons, however, communicate primarily through discontinuous spiking. We review methods for transferring our ability to construct interesting networks that perform relevant tasks from the artificial continuous domain to more realistic spiking network models. These methods raise a number of issues that warrant further theoretical and experimental study.
Development of Light Powered Sensor Networks for Thermal Comfort Measurement
Directory of Open Access Journals (Sweden)
Dasheng Lee
2008-10-01
Full Text Available Recent technological advances in wireless communications have enabled easy installation of sensor networks with air conditioning equipment control applications. However, the sensor node power supply, through either power lines or battery power, still presents obstacles to the distribution of the sensing systems. In this study, a novel sensor network, powered by the artificial light, was constructed to achieve wireless power transfer and wireless data communications for thermal comfort measurements. The sensing node integrates an IC-based temperature sensor, a radiation thermometer, a relative humidity sensor, a micro machined flow sensor and a microprocessor for predicting mean vote (PMV calculation. The 935 MHz band RF module was employed for the wireless data communication with a specific protocol based on a special energy beacon enabled mode capable of achieving zero power consumption during the inactive periods of the nodes. A 5W spotlight, with a dual axis tilt platform, can power the distributed nodes over a distance of up to 5 meters. A special algorithm, the maximum entropy method, was developed to estimate the sensing quantity of climate parameters if the communication module did not receive any response from the distributed nodes within a certain time limit. The light-powered sensor networks were able to gather indoor comfort-sensing index levels in good agreement with the comfort-sensing vote (CSV preferred by a human being and the experimental results within the environment suggested that the sensing system could be used in air conditioning systems to implement a comfort-optimal control strategy.
SPLAI: Computational Finite Element Model for Sensor Networks
Directory of Open Access Journals (Sweden)
Ruzana Ishak
2006-01-01
Full Text Available Wireless sensor network refers to a group of sensors, linked by a wireless medium to perform distributed sensing task. The primary interest is their capability in monitoring the physical environment through the deployment of numerous tiny, intelligent, wireless networked sensor nodes. Our interest consists of a sensor network, which includes a few specialized nodes called processing elements that can perform some limited computational capabilities. In this paper, we propose a model called SPLAI that allows the network to compute a finite element problem where the processing elements are modeled as the nodes in the linear triangular approximation problem. Our model also considers the case of some failures of the sensors. A simulation model to visualize this network has been developed using C++ on the Windows environment.
Parametric study of closed wet cooling tower thermal performance
Qasim, S. M.; Hayder, M. J.
2017-08-01
The present study involves experimental and theoretical analysis to evaluate the thermal performance of modified Closed Wet Cooling Tower (CWCT). The experimental study includes: design, manufacture and testing prototype of a modified counter flow forced draft CWCT. The modification based on addition packing to the conventional CWCT. A series of experiments was carried out at different operational parameters. In view of energy analysis, the thermal performance parameters of the tower are: cooling range, tower approach, cooling capacity, thermal efficiency, heat and mass transfer coefficients. The theoretical study included develops Artificial Neural Network (ANN) models to predicting various thermal performance parameters of the tower. Utilizing experimental data for training and testing, the models simulated by multi-layer back propagation algorithm for varying all operational parameters stated in experimental test.
Campus network security model study
Zhang, Yong-ku; Song, Li-ren
2011-12-01
Campus network security is growing importance, Design a very effective defense hacker attacks, viruses, data theft, and internal defense system, is the focus of the study in this paper. This paper compared the firewall; IDS based on the integrated, then design of a campus network security model, and detail the specific implementation principle.
Mahmood, Asif; Aziz, Asim; Jamshed, Wasim; Hussain, Sajid
Solar energy is the cleanest, renewable and most abundant source of energy available on earth. The main use of solar energy is to heat and cool buildings, heat water and to generate electricity. There are two types of solar energy collection system, the photovoltaic systems and the solar thermal collectors. The efficiency of any solar thermal system depend on the thermophysical properties of the operating fluids and the geometry/length of the system in which fluid is flowing. In the present research a simplified mathematical model for the solar thermal collectors is considered in the form of non-uniform unsteady stretching surface. The flow is induced by a non-uniform stretching of the porous sheet and the uniform magnetic field is applied in the transverse direction to the flow. The non-Newtonian Maxwell fluid model is utilized for the working fluid along with slip boundary conditions. Moreover the high temperature effect of thermal radiation and temperature dependent thermal conductivity are also included in the present model. The mathematical formulation is carried out through a boundary layer approach and the numerical computations are carried out for cu-water and TiO2 -water nanofluids. Results are presented for the velocity and temperature profiles as well as the skin friction coefficient and Nusselt number and the discussion is concluded on the effect of various governing parameters on the motion, temperature variation, velocity gradient and the rate of heat transfer at the boundary.
Thermal Analysis of a Finite Element Model in a Radiation Dominated Environment
Page, Arthur T.
2001-01-01
This paper presents a brief overview of thermal analysis, evaluating the University of Arizona mirror design, for the Next Generation Space Telescope (NGST) Pre-Phase A vehicle concept. Model building begins using Thermal Desktop(TM), by Cullimore and Ring Technologies, to import a NASTRAN bulk data file from the structural model of the mirror assembly. Using AutoCAD(R) capabilities, additional surfaces are added to simulate the thermal aspects of the problem which, for due reason, are not part of the structural model. Surfaces are then available to accept thermophysical and thermo-optical properties. Thermal Desktop(TM) calculates radiation conductors using Monte Carlo simulations. Then Thermal Desktop(TM) generates the SINDA input file having a one-to-one correspondence with the NASTRAN node and element definitions. A model is now available to evaluate the mirror design in the radiation dominated environment, conduct parametric trade studies of the thermal design, and provide temperatures to the finite element structural model.
Functional model of biological neural networks.
Lo, James Ting-Ho
2010-12-01
A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate neurons of the first type, supervised and unsupervised Hebbian learning mechanisms for easy learning and retrieving, an arrangement of dendritic trees for maximizing generalization, hardwiring for rotation-translation-scaling invariance, and feedback connections with different delay durations for neurons to make full use of present and past informations generated by neurons in the same and higher layers. These functional models and their processing operations have many functions of biological neural networks that have not been achieved by other models in the open literature and provide logically coherent answers to many long-standing neuroscientific questions. However, biological justifications of these functional models and their processing operations are required for THPAM to qualify as a macroscopic model (or low-order approximate) of biological neural networks.
Hydrodynamic and thermal modelling of gas-particle flow in fluidized beds
International Nuclear Information System (INIS)
Abdelkawi, O.S; Abdalla, A.M.; Atwan, E.F; Abdelmonem, S.A.; Elshazly, K.M.
2009-01-01
In this study a mathematical model has been developed to simulate two dimensional fluidized bed with uniform fluidization. The model consists of two sub models for hydrodynamic and thermal behavior of fluidized bed on which a FORTRAN program entitled (NEWFLUIDIZED) is devolved. The program is used to predict the volume fraction of gas and particle phases, the velocity of the two phases, the gas pressure and the temperature distribution for two phases. Also the program calculates the heat transfer coefficient. Besides the program predicts the fluidized bed stability and determines the optimum input gas velocity for fluidized bed to achieve the best thermal behavior. The hydrodynamic model is verified by comparing its results with the computational fluid dynamic code MFIX . While the thermal model was tested and compared by the available previous experimental correlations.The model results show good agreement with MFIX results and the thermal model of the present work confirms Zenz and Gunn equations
Stability of a neural network model with small-world connections
International Nuclear Information System (INIS)
Li Chunguang; Chen Guanrong
2003-01-01
Small-world networks are highly clustered networks with small distances among the nodes. There are many biological neural networks that present this kind of connection. There are no special weightings in the connections of most existing small-world network models. However, this kind of simply connected model cannot characterize biological neural networks, in which there are different weights in synaptic connections. In this paper, we present a neural network model with weighted small-world connections and further investigate the stability of this model
Combinatorial explosion in model gene networks
Edwards, R.; Glass, L.
2000-09-01
The explosive growth in knowledge of the genome of humans and other organisms leaves open the question of how the functioning of genes in interacting networks is coordinated for orderly activity. One approach to this problem is to study mathematical properties of abstract network models that capture the logical structures of gene networks. The principal issue is to understand how particular patterns of activity can result from particular network structures, and what types of behavior are possible. We study idealized models in which the logical structure of the network is explicitly represented by Boolean functions that can be represented by directed graphs on n-cubes, but which are continuous in time and described by differential equations, rather than being updated synchronously via a discrete clock. The equations are piecewise linear, which allows significant analysis and facilitates rapid integration along trajectories. We first give a combinatorial solution to the question of how many distinct logical structures exist for n-dimensional networks, showing that the number increases very rapidly with n. We then outline analytic methods that can be used to establish the existence, stability and periods of periodic orbits corresponding to particular cycles on the n-cube. We use these methods to confirm the existence of limit cycles discovered in a sample of a million randomly generated structures of networks of 4 genes. Even with only 4 genes, at least several hundred different patterns of stable periodic behavior are possible, many of them surprisingly complex. We discuss ways of further classifying these periodic behaviors, showing that small mutations (reversal of one or a few edges on the n-cube) need not destroy the stability of a limit cycle. Although these networks are very simple as models of gene networks, their mathematical transparency reveals relationships between structure and behavior, they suggest that the possibilities for orderly dynamics in such
Continuum Modeling of Biological Network Formation
Albi, Giacomo
2017-04-10
We present an overview of recent analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transportation networks. The model describes the pressure field using a Darcy type equation and the dynamics of the conductance network under pressure force effects. Randomness in the material structure is represented by a linear diffusion term and conductance relaxation by an algebraic decay term. We first introduce micro- and mesoscopic models and show how they are connected to the macroscopic PDE system. Then, we provide an overview of analytical results for the PDE model, focusing mainly on the existence of weak and mild solutions and analysis of the steady states. The analytical part is complemented by extensive numerical simulations. We propose a discretization based on finite elements and study the qualitative properties of network structures for various parameter values.
Physical and mathematical models for diffusion of thermal pollutants in water
International Nuclear Information System (INIS)
Pires, E.C.; Giorgetti, M.F.; Carajilescov, P.
1983-01-01
Mathematical models, such as the Fickian model and the model at PAILY and SAYRE, have been used in the analysis of thermal pollution. In the present work, experimental simulations of thermal dispersion were made using an artificial channel with injection of hat water and measurements of the temperature field were taken. The results were compared with the results given by the mentioned models, applying the image sources method. Due to the limitations of the model of PAILY and SAYRE, it was generalized for thermal sources posicioned at any place in the channel. The model of PAILY and SAYRE proved to be more satisfactory than the Fickian model and the image sources method was considered adequate. (Author) [pt
Nonlinear Modeling and Simulation of Thermal Effects in Microcantilever Resonators Dynamic
International Nuclear Information System (INIS)
Tadayon, M A; Sayyaadi, H; Jazar, G Nakhaie
2006-01-01
Thermal dependency of material characteristics in micro electromechanical systems strongly affects their performance, design, and control. Hence, it is essential to understand and model that in MEMS devices to optimize their designs. A thermal phenomenon introduces two main effects: damping due to internal friction, and softening due to Young modulus temperature relation. Based on some reported theoretical and experimental results, we model the thermal phenomena and use two Lorentzian functions to describe the restoring and damping forces caused by thermal phenomena. In order to emphasize the thermal effects, a nonlinear model of the MEMS, by considering capacitor nonlinearity, have been used. The response of the system is developed by employing multiple time scales perturbation method on nondimensionalized form of equations. Frequency response, resonant frequency and peak amplitude are examined for variation of dynamic parameters involved
Thermal modeling of the ceramic composite fuel for light water reactors
International Nuclear Information System (INIS)
Revankar, S.T.; Latta, R.; Solomon, A.A.
2005-01-01
Full text of publication follows: Composite fuel designs capable of providing improved thermal performance are of great interest in advanced reactor designs where high efficiency and long fuel cycles are desired. Thermal modeling of the composite fuel consisting of continuous second phase in a ceramic (uranium oxide) matrix has been carried out with detailed examination of the microstructure of the composite and the interface. Assuming that constituent phases are arranged as slabs, upper and lower bounds for the thermal conductivity of the composite are derived analytically. Bounding calculations on the thermal conductivity of the composite were performed for SiC dispersed in the UO 2 matrix. It is found that with 10% SiC, the thermal conductivity increases from 5.8 to 9.8 W/m.deg. K at 500 K, or an increase of 69% was observed in UO 2 matrix. The finite element analysis computer program ANSYS was used to create composite fuel geometries with set boundary conditions to produce accurate thermal conductivity predictions. A model developed also accounts for SiC-matrix interface resistance and the addition of coatings or interaction barriers. The first set of calculations using the code was to model simple series and parallel fuel slab geometries, and then advance to inter-connected parallel pathways. The analytical calculations were compared with the ANSYS results. The geometry of the model was set up as a 1 cm long by 400 micron wide rectangle. This rectangle was then divided into one hundred sections with the first ninety percent of a single section being UO 2 and the remaining ten percent consisting of SiC. The model was then meshed using triangular type elements. The boundary conditions were set with the sides of the rectangle being adiabatic and having an assigned temperature at the end of the rectangle. A heat flux was then applied to one end of the model producing a temperature gradient. The effective thermal conductivity was then calculated using the geometry
Modelling the impact of social network on energy savings
International Nuclear Information System (INIS)
Du, Feng; Zhang, Jiangfeng; Li, Hailong; Yan, Jinyue; Galloway, Stuart; Lo, Kwok L.
2016-01-01
Highlights: • Energy saving propagation along a social network is modelled. • This model consists of a time evolving weighted directed network. • Network weights and information decay are applied in savings calculation. - Abstract: It is noted that human behaviour changes can have a significant impact on energy consumption, however, qualitative study on such an impact is still very limited, and it is necessary to develop the corresponding mathematical models to describe how much energy savings can be achieved through human engagement. In this paper a mathematical model of human behavioural dynamic interactions on a social network is derived to calculate energy savings. This model consists of a weighted directed network with time evolving information on each node. Energy savings from the whole network is expressed as mathematical expectation from probability theory. This expected energy savings model includes both direct and indirect energy savings of individuals in the network. The savings model is obtained by network weights and modified by the decay of information. Expected energy savings are calculated for cases where individuals in the social network are treated as a single information source or multiple sources. This model is tested on a social network consisting of 40 people. The results show that the strength of relations between individuals is more important to information diffusion than the number of connections individuals have. The expected energy savings of optimally chosen node can be 25.32% more than randomly chosen nodes at the end of the second month for the case of single information source in the network, and 16.96% more than random nodes for the case of multiple information sources. This illustrates that the model presented in this paper can be used to determine which individuals will have the most influence on the social network, which in turn provides a useful guide to identify targeted customers in energy efficiency technology rollout
Energy Technology Data Exchange (ETDEWEB)
Luscher, Darby J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2014-05-08
We detail a modeling approach to simulate the anisotropic thermal expansion of polycrystalline (1,3,5-triamino-2,4,6-trinitrobenzene) TATB-based explosives that utilizes microstructural information including porosity, crystal aspect ratio, and processing-induced texture. This report, the first in a series, focuses on nonlinear thermal expansion of “neat-pressed” polycrystalline TATB specimens which do not contain any binder; additional complexities related to polymeric binder and irreversible ratcheting behavior are briefly discussed, however detailed investigation of these aspects are deferred to subsequent reports. In this work we have, for the first time, developed a mesoscale continuum model relating the thermal expansion of polycrystal TATB specimens to their microstructural characteristics. A self-consistent homogenization procedure is used to relate macroscopic thermoelastic response to the constitutive behavior of single-crystal TATB. The model includes a representation of grain aspect ratio, porosity, and crystallographic texture attributed to the consolidation process. A quantitative model is proposed to describe the evolution of preferred orientation of graphitic planes in TATB during consolidation and an algorithm constructed to develop a discrete representation of the associated orientation distribution function. Analytical and numerical solutions using this model are shown to produce textures consistent with previous measurements and characterization for isostatic and uniaxial “die-pressed” specimens. Predicted thermal strain versus temperature for textured specimens are shown to be in agreement with corresponding experimental measurements. Using the developed modeling approach, several simulations have been run to investigate the influence of microstructure on macroscopic thermal expansion behavior. Results from these simulations are used to identify qualitative trends. Implications of the identified trends are discussed in the context of
Settings in Social Networks : a Measurement Model
Schweinberger, Michael; Snijders, Tom A.B.
2003-01-01
A class of statistical models is proposed that aims to recover latent settings structures in social networks. Settings may be regarded as clusters of vertices. The measurement model is based on two assumptions. (1) The observed network is generated by hierarchically nested latent transitive
An endogenous model of the credit network
He, Jianmin; Sui, Xin; Li, Shouwei
2016-01-01
In this paper, an endogenous credit network model of firm-bank agents is constructed. The model describes the endogenous formation of firm-firm, firm-bank and bank-bank credit relationships. By means of simulations, the model is capable of showing some obvious similarities with empirical evidence found by other scholars: the upper-tail of firm size distribution can be well fitted with a power-law; the bank size distribution can be lognormally distributed with a power-law tail; the bank in-degrees of the interbank credit network as well as the firm-bank credit network fall into two-power-law distributions.
Power Loss Calculation and Thermal Modelling for a Three Phase Inverter Drive System
Directory of Open Access Journals (Sweden)
Z. Zhou
2005-12-01
Full Text Available Power losses calculation and thermal modelling for a three-phase inverter power system is presented in this paper. Aiming a long real time thermal simulation, an accurate average power losses calculation based on PWM reconstruction technique is proposed. For carrying out the thermal simulation, a compact thermal model for a three-phase inverter power module is built. The thermal interference of adjacent heat sources is analysed using 3D thermal simulation. The proposed model can provide accurate power losses with a large simulation time-step and suitable for a long real time thermal simulation for a three phase inverter drive system for hybrid vehicle applications.
A last updating evolution model for online social networks
Bu, Zhan; Xia, Zhengyou; Wang, Jiandong; Zhang, Chengcui
2013-05-01
As information technology has advanced, people are turning to electronic media more frequently for communication, and social relationships are increasingly found on online channels. However, there is very limited knowledge about the actual evolution of the online social networks. In this paper, we propose and study a novel evolution network model with the new concept of “last updating time”, which exists in many real-life online social networks. The last updating evolution network model can maintain the robustness of scale-free networks and can improve the network reliance against intentional attacks. What is more, we also found that it has the “small-world effect”, which is the inherent property of most social networks. Simulation experiment based on this model show that the results and the real-life data are consistent, which means that our model is valid.
Mathematical modelling of complex contagion on clustered networks
O'sullivan, David J.; O'Keeffe, Gary; Fennell, Peter; Gleeson, James
2015-09-01
The spreading of behavior, such as the adoption of a new innovation, is influenced bythe structure of social networks that interconnect the population. In the experiments of Centola (Science, 2010), adoption of new behavior was shown to spread further and faster across clustered-lattice networks than across corresponding random networks. This implies that the “complex contagion” effects of social reinforcement are important in such diffusion, in contrast to “simple” contagion models of disease-spread which predict that epidemics would grow more efficiently on random networks than on clustered networks. To accurately model complex contagion on clustered networks remains a challenge because the usual assumptions (e.g. of mean-field theory) regarding tree-like networks are invalidated by the presence of triangles in the network; the triangles are, however, crucial to the social reinforcement mechanism, which posits an increased probability of a person adopting behavior that has been adopted by two or more neighbors. In this paper we modify the analytical approach that was introduced by Hebert-Dufresne et al. (Phys. Rev. E, 2010), to study disease-spread on clustered networks. We show how the approximation method can be adapted to a complex contagion model, and confirm the accuracy of the method with numerical simulations. The analytical results of the model enable us to quantify the level of social reinforcement that is required to observe—as in Centola’s experiments—faster diffusion on clustered topologies than on random networks.
Mathematical modelling of complex contagion on clustered networks
Directory of Open Access Journals (Sweden)
David J. P. O'Sullivan
2015-09-01
Full Text Available The spreading of behavior, such as the adoption of a new innovation, is influenced bythe structure of social networks that interconnect the population. In the experiments of Centola (Science, 2010, adoption of new behavior was shown to spread further and faster across clustered-lattice networks than across corresponding random networks. This implies that the complex contagion effects of social reinforcement are important in such diffusion, in contrast to simple contagion models of disease-spread which predict that epidemics would grow more efficiently on random networks than on clustered networks. To accurately model complex contagion on clustered networks remains a challenge because the usual assumptions (e.g. of mean-field theory regarding tree-like networks are invalidated by the presence of triangles in the network; the triangles are, however, crucial to the social reinforcement mechanism, which posits an increased probability of a person adopting behavior that has been adopted by two or more neighbors. In this paper we modify the analytical approach that was introduced by Hebert-Dufresne et al. (Phys. Rev. E, 2010, to study disease-spread on clustered networks. We show how the approximation method can be adapted to a complex contagion model, and confirm the accuracy of the method with numerical simulations. The analytical results of the model enable us to quantify the level of social reinforcement that is required to observe—as in Centola’s experiments—faster diffusion on clustered topologies than on random networks.
Phenomenological network models: Lessons for epilepsy surgery.
Hebbink, Jurgen; Meijer, Hil; Huiskamp, Geertjan; van Gils, Stephan; Leijten, Frans
2017-10-01
The current opinion in epilepsy surgery is that successful surgery is about removing pathological cortex in the anatomic sense. This contrasts with recent developments in epilepsy research, where epilepsy is seen as a network disease. Computational models offer a framework to investigate the influence of networks, as well as local tissue properties, and to explore alternative resection strategies. Here we study, using such a model, the influence of connections on seizures and how this might change our traditional views of epilepsy surgery. We use a simple network model consisting of four interconnected neuronal populations. One of these populations can be made hyperexcitable, modeling a pathological region of cortex. Using model simulations, the effect of surgery on the seizure rate is studied. We find that removal of the hyperexcitable population is, in most cases, not the best approach to reduce the seizure rate. Removal of normal populations located at a crucial spot in the network, the "driver," is typically more effective in reducing seizure rate. This work strengthens the idea that network structure and connections may be more important than localizing the pathological node. This can explain why lesionectomy may not always be sufficient. © 2017 The Authors. Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy.
A temperature dependent slip factor based thermal model for friction
Indian Academy of Sciences (India)
This paper proposes a new slip factor based three-dimensional thermal model to predict the temperature distribution during friction stir welding of 304L stainless steel plates. The proposed model employs temperature and radius dependent heat source to study the thermal cycle, temperature distribution, power required, the ...
Dynamic Pathloss Model for Future Mobile Communication Networks
DEFF Research Database (Denmark)
Kumar, Ambuj; Mihovska, Albena Dimitrova; Prasad, Ramjee
2016-01-01
that are essentially static. Therefore, once the signal level drops beyond the predicted values due to any variance in the environmental conditions, very crowded areas may not be catered well enough by the deployed network that had been designed with the static path loss model. This paper proposes an approach......— Future mobile communication networks (MCNs) are expected to be more intelligent and proactive based on new capabilities that increase agility and performance. However, for any successful mobile network service, the dexterity in network deployment is a key factor. The efficiency of the network...... planning depends on how congruent the chosen path loss model and real propagation are. Various path loss models have been developed that predict the signal propagation in various morphological and climatic environments; however they consider only those physical parameters of the network environment...
Modeling the reemergence of information diffusion in social network
Yang, Dingda; Liao, Xiangwen; Shen, Huawei; Cheng, Xueqi; Chen, Guolong
2018-01-01
Information diffusion in networks is an important research topic in various fields. Existing studies either focus on modeling the process of information diffusion, e.g., independent cascade model and linear threshold model, or investigate information diffusion in networks with certain structural characteristics such as scale-free networks and small world networks. However, there are still several phenomena that have not been captured by existing information diffusion models. One of the prominent phenomena is the reemergence of information diffusion, i.e., a piece of information reemerges after the completion of its initial diffusion process. In this paper, we propose an optimized information diffusion model by introducing a new informed state into traditional susceptible-infected-removed model. We verify the proposed model via simulations in real-world social networks, and the results indicate that the model can reproduce the reemergence of information during the diffusion process.
Zulkifli; Wiryawan, G. P.
2018-03-01
Lightweight brick is the most important component of building construction, therefore it is necessary to have lightweight thermal, mechanical and aqustic thermal properties that meet the standard, in this paper which is discussed is the domain of light brick thermal conductivity properties. The advantage of lightweight brick has a low density (500-650 kg/m3), more economical, can reduce the load 30-40% compared to conventional brick (clay brick). In this research, Artificial Neural Network (ANN) is used to predict the thermal conductivity of lightweight brick type Autoclaved Aerated Concrete (AAC). Based on the training and evaluation that have been done on 10 model of ANN with number of hidden node 1 to 10, obtained that ANN with 3 hidden node have the best performance. It is known from the mean value of MSE (Mean Square Error) validation for three training times of 0.003269. This ANN was further used to predict the thermal conductivity of four light brick samples. The predicted results for each of the AAC1, AAC2, AAC3 and AAC4 light brick samples were 0.243 W/m.K, respectively; 0.29 W/m.K; 0.32 W/m.K; and 0.32 W/m.K. Furthermore, ANN is used to determine the effect of silicon composition (Si), Calcium (Ca), to light brick thermal conductivity. ANN simulation results show that the thermal conductivity increases with increasing Si composition. Si content is allowed maximum of 26.57%, while the Ca content in the range 20.32% - 30.35%.
Joint Modelling of Structural and Functional Brain Networks
DEFF Research Database (Denmark)
Andersen, Kasper Winther; Herlau, Tue; Mørup, Morten
-parametric Bayesian network model which allows for joint modelling and integration of multiple networks. We demonstrate the model’s ability to detect vertices that share structure across networks jointly in functional MRI (fMRI) and diffusion MRI (dMRI) data. Using two fMRI and dMRI scans per subject, we establish...
Spontaneous non-thermal leptogenesis in high-scale inflation models
International Nuclear Information System (INIS)
Endo, M.; Takahashi, F.; Yanagida, T.T.; Tokyo Univ.
2006-11-01
We argue that a non-thermal leptogenesis occurs spontaneously, without direct couplings of the inflation with right-handed neutrinos, in a wide class of high-scale inflation models such as the chaotic and hybrid inflation. It is only a finite vacuum expectation value of the inflaton, of more precisely, a linear term in the Kaehler potential, that is a prerequisite for the spontaneous non-thermal leptogenesis. To exemplify how it works, we show that a chaotic inflation model in supergravity naturally produces a right amount of baryon asymmetry via the spontaneous non-thermal leptogenesis. We also discuss the gravitino production from the inflation. (orig.)
Performance modeling of network data services
Energy Technology Data Exchange (ETDEWEB)
Haynes, R.A.; Pierson, L.G.
1997-01-01
Networks at major computational organizations are becoming increasingly complex. The introduction of large massively parallel computers and supercomputers with gigabyte memories are requiring greater and greater bandwidth for network data transfers to widely dispersed clients. For networks to provide adequate data transfer services to high performance computers and remote users connected to them, the networking components must be optimized from a combination of internal and external performance criteria. This paper describes research done at Sandia National Laboratories to model network data services and to visualize the flow of data from source to sink when using the data services.
System-level Modeling of Wireless Integrated Sensor Networks
DEFF Research Database (Denmark)
Virk, Kashif M.; Hansen, Knud; Madsen, Jan
2005-01-01
Wireless integrated sensor networks have emerged as a promising infrastructure for a new generation of monitoring and tracking applications. In order to efficiently utilize the extremely limited resources of wireless sensor nodes, accurate modeling of the key aspects of wireless sensor networks...... is necessary so that system-level design decisions can be made about the hardware and the software (applications and real-time operating system) architecture of sensor nodes. In this paper, we present a SystemC-based abstract modeling framework that enables system-level modeling of sensor network behavior...... by modeling the applications, real-time operating system, sensors, processor, and radio transceiver at the sensor node level and environmental phenomena, including radio signal propagation, at the sensor network level. We demonstrate the potential of our modeling framework by simulating and analyzing a small...
THERMUS—A thermal model package for ROOT
Wheaton, S.; Cleymans, J.; Hauer, M.
2009-01-01
THERMUS is a package of C++ classes and functions allowing statistical-thermal model analyses of particle production in relativistic heavy-ion collisions to be performed within the ROOT framework of analysis. Calculations are possible within three statistical ensembles; a grand-canonical treatment of the conserved charges B, S and Q, a fully canonical treatment of the conserved charges, and a mixed-canonical ensemble combining a canonical treatment of strangeness with a grand-canonical treatment of baryon number and electric charge. THERMUS allows for the assignment of decay chains and detector efficiencies specific to each particle yield, which enables sensible fitting of model parameters to experimental data. Program summaryProgram title: THERMUS, version 2.1 Catalogue identifier: AEBW_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBW_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 17 152 No. of bytes in distributed program, including test data, etc.: 93 581 Distribution format: tar.gz Programming language: C++ Computer: PC, Pentium 4, 1 GB RAM (not hardware dependent) Operating system: Linux: FEDORA, RedHat, etc. Classification: 17.7 External routines: Numerical Recipes in C [1], ROOT [2] Nature of problem: Statistical-thermal model analyses of heavy-ion collision data require the calculation of both primordial particle densities and contributions from resonance decay. A set of thermal parameters (the number depending on the particular model imposed) and a set of thermalized particles, with their decays specified, is required as input to these models. The output is then a complete set of primordial thermal quantities for each particle, together with the contributions to the final particle yields from resonance decay. In many applications of
Theoretical Modelling Methods for Thermal Management of Batteries
Directory of Open Access Journals (Sweden)
Bahman Shabani
2015-09-01
Full Text Available The main challenge associated with renewable energy generation is the intermittency of the renewable source of power. Because of this, back-up generation sources fuelled by fossil fuels are required. In stationary applications whether it is a back-up diesel generator or connection to the grid, these systems are yet to be truly emissions-free. One solution to the problem is the utilisation of electrochemical energy storage systems (ESS to store the excess renewable energy and then reusing this energy when the renewable energy source is insufficient to meet the demand. The performance of an ESS amongst other things is affected by the design, materials used and the operating temperature of the system. The operating temperature is critical since operating an ESS at low ambient temperatures affects its capacity and charge acceptance while operating the ESS at high ambient temperatures affects its lifetime and suggests safety risks. Safety risks are magnified in renewable energy storage applications given the scale of the ESS required to meet the energy demand. This necessity has propelled significant effort to model the thermal behaviour of ESS. Understanding and modelling the thermal behaviour of these systems is a crucial consideration before designing an efficient thermal management system that would operate safely and extend the lifetime of the ESS. This is vital in order to eliminate intermittency and add value to renewable sources of power. This paper concentrates on reviewing theoretical approaches used to simulate the operating temperatures of ESS and the subsequent endeavours of modelling thermal management systems for these systems. The intent of this review is to present some of the different methods of modelling the thermal behaviour of ESS highlighting the advantages and disadvantages of each approach.
An evolving model of online bipartite networks
Zhang, Chu-Xu; Zhang, Zi-Ke; Liu, Chuang
2013-12-01
Understanding the structure and evolution of online bipartite networks is a significant task since they play a crucial role in various e-commerce services nowadays. Recently, various attempts have been tried to propose different models, resulting in either power-law or exponential degree distributions. However, many empirical results show that the user degree distribution actually follows a shifted power-law distribution, the so-called Mandelbrot’s law, which cannot be fully described by previous models. In this paper, we propose an evolving model, considering two different user behaviors: random and preferential attachment. Extensive empirical results on two real bipartite networks, Delicious and CiteULike, show that the theoretical model can well characterize the structure of real networks for both user and object degree distributions. In addition, we introduce a structural parameter p, to demonstrate that the hybrid user behavior leads to the shifted power-law degree distribution, and the region of power-law tail will increase with the increment of p. The proposed model might shed some lights in understanding the underlying laws governing the structure of real online bipartite networks.
Volpi, Giorgio; Riva, Federico; Frattini, Paolo; Battista Crosta, Giovanni; Magri, Fabien
2016-04-01
Thermal springs are widespread in the European Alps, where more than 80 geothermal sites are known and exploited. The quantitative assessment of those thermal flow systems is a challenging issue and requires accurate conceptual model and a thorough understanding of thermo-hydraulic properties of the aquifers. Accordingly in the last years, several qualitative studies were carried out to understand the heat and fluid transport processes driving deep fluids from the reservoir to the springs. Our work focused on thermal circulation and fluid outflows of the area around Bormio (Central Italian Alps), where nine geothermal springs discharge from dolomite bodies located close to a regional alpine thrust, called the Zebrù Line. At this site, water is heated in deep circulation systems and vigorously upwells at temperature of about 40°C. The aim of this paper is to explore the mechanisms of heat and fluid transport in the Bormio area by carrying out refined steady and transient three-dimensional finite element simulations of thermally-driven flow and to quantitatively assess the source area of the thermal waters. The full regional model (ca. 700 km2) is discretized with a highly refined triangular finite element planar grid obtained with Midas GTS NX software. The structural 3D features of the regional Zebrù thrust are built by interpolating series of geological cross sections using Fracman. A script was developed to convert and implement the thrust grid into FEFLOW mesh that comprises ca. 4 million elements. The numerical results support the observed discharge rates and temperature field within the simulated domain. Flow and temperature patterns suggest that thermal groundwater flows through a deep system crossing both sedimentary and metamorphic lithotypes, and a fracture network associated to the thrust system. Besides providing a numerical framework to simulate complex fractured systems, this example gives insights into the influence of deep alpine structures on
A Temperature-Dependent Thermal Model of IGBT Modules Suitable for Circuit-Level Simulations
DEFF Research Database (Denmark)
Wu, Rui; Wang, Huai; Ma, Ke
2014-01-01
Thermal impedance of IGBT modules may vary with operating conditions due to that the thermal conductivity and heat capacity of materials are temperature dependent. This paper proposes a Cauer thermal model for a 1700 V/1000 A IGBT module with temperature-dependent thermal resistances and thermal ...... relevant reliability aspect performance. A test bench is built up with an ultra-fast infrared (IR) camera to validate the proposed thermal impedance model....
Models as Tools of Analysis of a Network Organisation
Directory of Open Access Journals (Sweden)
Wojciech Pająk
2013-06-01
Full Text Available The paper presents models which may be applied as tools of analysis of a network organisation. The starting point of the discussion is defining the following terms: supply chain and network organisation. Further parts of the paper present basic assumptions analysis of a network organisation. Then the study characterises the best known models utilised in analysis of a network organisation. The purpose of the article is to define the notion and the essence of network organizations and to present the models used for their analysis.
Systems and methods for modeling and analyzing networks
Hill, Colin C; Church, Bruce W; McDonagh, Paul D; Khalil, Iya G; Neyarapally, Thomas A; Pitluk, Zachary W
2013-10-29
The systems and methods described herein utilize a probabilistic modeling framework for reverse engineering an ensemble of causal models, from data and then forward simulating the ensemble of models to analyze and predict the behavior of the network. In certain embodiments, the systems and methods described herein include data-driven techniques for developing causal models for biological networks. Causal network models include computational representations of the causal relationships between independent variables such as a compound of interest and dependent variables such as measured DNA alterations, changes in mRNA, protein, and metabolites to phenotypic readouts of efficacy and toxicity.
Modeling and optimization of an electric power distribution network ...
African Journals Online (AJOL)
Modeling and optimization of an electric power distribution network planning system using ... of the network was modelled with non-linear mathematical expressions. ... given feasible locations, re-conductoring of existing feeders in the network, ...
Directory of Open Access Journals (Sweden)
Haibo Zhang
2016-08-01
Full Text Available The security incidents ion networks are sudden and uncertain, it is very hard to precisely predict the network security situation by traditional methods. In order to improve the prediction accuracy of the network security situation, we build a network security situation prediction model based on Wavelet Neural Network (WNN with optimized parameters by the Improved Niche Genetic Algorithm (INGA. The proposed model adopts WNN which has strong nonlinear ability and fault-tolerance performance. Also, the parameters for WNN are optimized through the adaptive genetic algorithm (GA so that WNN searches more effectively. Considering the problem that the adaptive GA converges slowly and easily turns to the premature problem, we introduce a novel niche technology with a dynamic fuzzy clustering and elimination mechanism to solve the premature convergence of the GA. Our final simulation results show that the proposed INGA-WNN prediction model is more reliable and effective, and it achieves faster convergence-speed and higher prediction accuracy than the Genetic Algorithm-Wavelet Neural Network (GA-WNN, Genetic Algorithm-Back Propagation Neural Network (GA-BPNN and WNN.
Modeling thermal effects in braking systems of railway vehicles
Directory of Open Access Journals (Sweden)
Milošević Miloš S.
2012-01-01
Full Text Available The modeling of thermal effects has become increasingly important in product design in different transport means, road vehicles, airplanes, railway vehicles, and so forth. The thermal analysis is a very important stage in the study of braking systems, especially of railway vehicles, where it is necessary to brake huge masses, because the thermal load of a braked railway wheel prevails compared to other types of loads. In the braking phase, kinetic energy transforms into thermal energy resulting in intense heating and high temperature states of railway wheels. Thus induced thermal loads determine thermomechanical behavior of the structure of railway wheels. In cases of thermal overloads, which mainly occur as a result of long-term braking on down-grade railroads, the generation of stresses and deformations occurs, whose consequences are the appearance of cracks on the rim of a wheel and the final total wheel defect. The importance to precisely determine the temperature distribution caused by the transfer process of the heat generated during braking due to the friction on contact surfaces of the braking system makes it a challenging research task. Therefore, the thermal analysis of a block-braked solid railway wheel of a 444 class locomotive of the national railway operator Serbian Railways is processed in detail in this paper, using analytical and numerical modeling of thermal effects during long-term braking for maintaining a constant speed on a down-grade railroad.
Asteroid thermal modeling in the presence of reflected sunlight
Myhrvold, Nathan
2018-03-01
A new derivation of simple asteroid thermal models is presented, investigating the need to account correctly for Kirchhoff's law of thermal radiation when IR observations contain substantial reflected sunlight. The framework applies to both the NEATM and related thermal models. A new parameterization of these models eliminates the dependence of thermal modeling on visible absolute magnitude H, which is not always available. Monte Carlo simulations are used to assess the potential impact of violating Kirchhoff's law on estimates of physical parameters such as diameter and IR albedo, with an emphasis on NEOWISE results. The NEOWISE papers use ten different models, applied to 12 different combinations of WISE data bands, in 47 different combinations. The most prevalent combinations are simulated and the accuracy of diameter estimates is found to be depend critically on the model and data band combination. In the best case of full thermal modeling of all four band the errors in an idealized model the 1σ (68.27%) confidence interval is -5% to +6%, but this combination is just 1.9% of NEOWISE results. Other combinations representing 42% of the NEOWISE results have about twice the CI at -10% to +12%, before accounting for errors due to irregular shape or other real world effects that are not simulated. The model and data band combinations found for the majority of NEOWISE results have much larger systematic and random errors. Kirchhoff's law violation by NEOWISE models leads to errors in estimation accuracy that are strongest for asteroids with W1, W2 band emissivity ɛ12 in both the lowest (0.605 ≤ɛ12 ≤ 0 . 780), and highest decile (0.969 ≤ɛ12 ≤ 0 . 988), corresponding to the highest and lowest deciles of near-IR albedo pIR. Systematic accuracy error between deciles ranges from a low of 5% to as much as 45%, and there are also differences in the random errors. Kirchhoff's law effects also produce large errors in NEOWISE estimates of pIR, particularly for high
Research on network information security model and system construction
Wang Haijun
2016-01-01
It briefly describes the impact of large data era on China’s network policy, but also brings more opportunities and challenges to the network information security. This paper reviews for the internationally accepted basic model and characteristics of network information security, and analyses the characteristics of network information security and their relationship. On the basis of the NIST security model, this paper describes three security control schemes in safety management model and the...
Modeling Temporal Evolution and Multiscale Structure in Networks
DEFF Research Database (Denmark)
Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard
2013-01-01
Many real-world networks exhibit both temporal evolution and multiscale structure. We propose a model for temporally correlated multifurcating hierarchies in complex networks which jointly capture both effects. We use the Gibbs fragmentation tree as prior over multifurcating trees and a change......-point model to account for the temporal evolution of each vertex. We demonstrate that our model is able to infer time-varying multiscale structure in synthetic as well as three real world time-evolving complex networks. Our modeling of the temporal evolution of hierarchies brings new insights...
Thermal unit availability modeling in a regional simulation model
International Nuclear Information System (INIS)
Yamayee, Z.A.; Port, J.; Robinett, W.
1983-01-01
The System Analysis Model (SAM) developed under the umbrella of PNUCC's System Analysis Committee is capable of simulating the operation of a given load/resource scenario. This model employs a Monte-Carlo simulation to incorporate uncertainties. Among uncertainties modeled is thermal unit availability both for energy simulation (seasonal) and capacity simulations (hourly). This paper presents the availability modeling in the capacity and energy models. The use of regional and national data in deriving the two availability models, the interaction between the two and modifications made to the capacity model in order to reflect regional practices is presented. A sample problem is presented to show the modification process. Results for modeling a nuclear unit using NERC-GADS is presented
The Kuramoto model in complex networks
Rodrigues, Francisco A.; Peron, Thomas K. DM.; Ji, Peng; Kurths, Jürgen
2016-01-01
Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. This model has been traditionally studied in complete graphs. However, besides being intrinsically dynamical, complex systems present very heterogeneous structure, which can be represented as complex networks. This report is dedicated to review main contributions in the field of synchronization in networks of Kuramoto oscillators. In particular, we provide an overview of the impact of network patterns on the local and global dynamics of coupled phase oscillators. We cover many relevant topics, which encompass a description of the most used analytical approaches and the analysis of several numerical results. Furthermore, we discuss recent developments on variations of the Kuramoto model in networks, including the presence of noise and inertia. The rich potential for applications is discussed for special fields in engineering, neuroscience, physics and Earth science. Finally, we conclude by discussing problems that remain open after the last decade of intensive research on the Kuramoto model and point out some promising directions for future research.
Mars Propellant Liquefaction Modeling in Thermal Desktop
Desai, Pooja; Hauser, Dan; Sutherlin, Steven
2017-01-01
NASAs current Mars architectures are assuming the production and storage of 23 tons of liquid oxygen on the surface of Mars over a duration of 500+ days. In order to do this in a mass efficient manner, an energy efficient refrigeration system will be required. Based on previous analysis NASA has decided to do all liquefaction in the propulsion vehicle storage tanks. In order to allow for transient Martian environmental effects, a propellant liquefaction and storage system for a Mars Ascent Vehicle (MAV) was modeled using Thermal Desktop. The model consisted of a propellant tank containing a broad area cooling loop heat exchanger integrated with a reverse turbo Brayton cryocooler. Cryocooler sizing and performance modeling was conducted using MAV diurnal heat loads and radiator rejection temperatures predicted from a previous thermal model of the MAV. A system was also sized and modeled using an alternative heat rejection system that relies on a forced convection heat exchanger. Cryocooler mass, input power, and heat rejection for both systems were estimated and compared against sizing based on non-transient sizing estimates.
Directory of Open Access Journals (Sweden)
Mohammad Taghi Ameli
2012-01-01
Full Text Available Transmission Network Expansion Planning (TNEP is a basic part of power network planning that determines where, when and how many new transmission lines should be added to the network. So, the TNEP is an optimization problem in which the expansion purposes are optimized. Artificial Intelligence (AI tools such as Genetic Algorithm (GA, Simulated Annealing (SA, Tabu Search (TS and Artificial Neural Networks (ANNs are methods used for solving the TNEP problem. Today, by using the hybridization models of AI tools, we can solve the TNEP problem for large-scale systems, which shows the effectiveness of utilizing such models. In this paper, a new approach to the hybridization model of Probabilistic Neural Networks (PNNs and Harmony Search Algorithm (HSA was used to solve the TNEP problem. Finally, by considering the uncertain role of the load based on a scenario technique, this proposed model was tested on the Garver’s 6-bus network.
Fractional Heat Conduction Models and Thermal Diffusivity Determination
Directory of Open Access Journals (Sweden)
Monika Žecová
2015-01-01
Full Text Available The contribution deals with the fractional heat conduction models and their use for determining thermal diffusivity. A brief historical overview of the authors who have dealt with the heat conduction equation is described in the introduction of the paper. The one-dimensional heat conduction models with using integer- and fractional-order derivatives are listed. Analytical and numerical methods of solution of the heat conduction models with using integer- and fractional-order derivatives are described. Individual methods have been implemented in MATLAB and the examples of simulations are listed. The proposal and experimental verification of the methods for determining thermal diffusivity using half-order derivative of temperature by time are listed at the conclusion of the paper.
Mathematical Modelling Plant Signalling Networks
Muraro, D.; Byrne, H.M.; King, J.R.; Bennett, M.J.
2013-01-01
methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more
A thermal conductivity model for U-Si compounds
Energy Technology Data Exchange (ETDEWEB)
Zhang, Yongfeng [Idaho National Lab. (INL), Idaho Falls, ID (United States); Andersson, Anders David Ragnar [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-02-02
U_{3}Si_{2} is a candidate for accident tolerant nuclear fuel being developed as an alternative to UO_{2} in commercial light water reactors (LWRs). One of its main benefits compared to UO_{2} is higher thermal conductivity that increases with temperature. This increase is contrary to UO_{2}, for which the thermal conductivity decreases with temperature. The reason for the difference is the electronic origin of thermal conductivity in U_{3}Si_{2}, as compared to the phonon mechanism responsible for thermal transport in UO_{2}. The phonon thermal conductivity in UO_{2} is unusually low for a fluorite oxide due to the strong interaction with the spins in the paramagnetic phase. The thermal conductivity of U_{3}Si_{2} as well as other U-Si compounds has been measured experimentally [1-4]. However, for fuel performance simulations it is also critical to model the degradation of the thermal conductivity due to damage and microstructure evolution caused by the reactor environment (irradiation and high temperature). For UO_{2} this reduction is substantial and it has been the topic of extensive NEAMS research resulting in several publications [5, 6]. There are no data or models for the evolution of the U_{3}Si_{2} thermal conductivity under irradiation. We know that the intrinsic thermal conductivities of UO_{2} (semi-conductor) and U_{3}Si_{2} (metal) are very different, and we do not necessarily expect the dependence on damage to be the same either, which could present another advantage for the silicide fuel. In this report we summarize the first step in developing a model for the thermal conductivity of U-Si compounds with the goal of capturing the effect of damage in U_{3}Si_{2}. Next year, we will focus on lattice damage. We will also attempt to assess the impact of fission gas bubbles.
Modeling solid thermal explosion containment on reactor HNIW and HMX
International Nuclear Information System (INIS)
Lin, Chun-Ping; Chang, Chang-Ping; Chou, Yu-Chuan; Chu, Yung-Chuan; Shu, Chi-Min
2010-01-01
2,4,6,8,10,12-Hexanitro-2,4,6,8,10,12-hexaaza-isowurtzitane (HNIW), also known as CL-20 and octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX), are highly energetic materials which have been popular in national defense industries for years. This study established the models of thermal decomposition and thermal explosion hazard for HNIW and HMX. Differential scanning calorimetry (DSC) data were used for parameters determination of the thermokinetic models, and then these models were employed for simulation of thermal explosion in a 437 L barrel reactor and a 24 kg cubic box package. Experimental results indicating the best storage conditions to avoid any violent runaway reaction of HNIW and HMX were also discovered. This study also developed an efficient procedure regarding creation of thermokinetics and assessment of thermal hazards of HNIW and HMX that could be applied to ensure safe storage conditions.
Evaluation of EOR Processes Using Network Models
DEFF Research Database (Denmark)
Winter, Anatol; Larsen, Jens Kjell; Krogsbøll, Anette
1998-01-01
The report consists of the following parts: 1) Studies of wetting properties of model fluids and fluid mixtures aimed at an optimal selection of candidates for micromodel experiments. 2) Experimental studies of multiphase transport properties using physical models of porous networks (micromodels......) including estimation of their "petrophysical" properties (e.g. absolute permeability). 3) Mathematical modelling and computer studies of multiphase transport through pore space using mathematical network models. 4) Investigation of link between pore-scale and macroscopic recovery mechanisms....
Modeling Insurgent Network Structure and Dynamics
Gabbay, Michael; Thirkill-Mackelprang, Ashley
2010-03-01
We present a methodology for mapping insurgent network structure based on their public rhetoric. Indicators of cooperative links between insurgent groups at both the leadership and rank-and-file levels are used, such as joint policy statements or joint operations claims. In addition, a targeting policy measure is constructed on the basis of insurgent targeting claims. Network diagrams which integrate these measures of insurgent cooperation and ideology are generated for different periods of the Iraqi and Afghan insurgencies. The network diagrams exhibit meaningful changes which track the evolution of the strategic environment faced by insurgent groups. Correlations between targeting policy and network structure indicate that insurgent targeting claims are aimed at establishing a group identity among the spectrum of rank-and-file insurgency supporters. A dynamical systems model of insurgent alliance formation and factionalism is presented which evolves the relationship between insurgent group dyads as a function of their ideological differences and their current relationships. The ability of the model to qualitatively and quantitatively capture insurgent network dynamics observed in the data is discussed.
Use of advanced modeling techniques to optimize thermal packaging designs.
Formato, Richard M; Potami, Raffaele; Ahmed, Iftekhar
2010-01-01
Through a detailed case study the authors demonstrate, for the first time, the capability of using advanced modeling techniques to correctly simulate the transient temperature response of a convective flow-based thermal shipper design. The objective of this case study was to demonstrate that simulation could be utilized to design a 2-inch-wall polyurethane (PUR) shipper to hold its product box temperature between 2 and 8 °C over the prescribed 96-h summer profile (product box is the portion of the shipper that is occupied by the payload). Results obtained from numerical simulation are in excellent agreement with empirical chamber data (within ±1 °C at all times), and geometrical locations of simulation maximum and minimum temperature match well with the corresponding chamber temperature measurements. Furthermore, a control simulation test case was run (results taken from identical product box locations) to compare the coupled conduction-convection model with a conduction-only model, which to date has been the state-of-the-art method. For the conduction-only simulation, all fluid elements were replaced with "solid" elements of identical size and assigned thermal properties of air. While results from the coupled thermal/fluid model closely correlated with the empirical data (±1 °C), the conduction-only model was unable to correctly capture the payload temperature trends, showing a sizeable error compared to empirical values (ΔT > 6 °C). A modeling technique capable of correctly capturing the thermal behavior of passively refrigerated shippers can be used to quickly evaluate and optimize new packaging designs. Such a capability provides a means to reduce the cost and required design time of shippers while simultaneously improving their performance. Another advantage comes from using thermal modeling (assuming a validated model is available) to predict the temperature distribution in a shipper that is exposed to ambient temperatures which were not bracketed
General 3D Lumped Thermal Model with Various Boundary Conditions for High Power IGBT Modules
DEFF Research Database (Denmark)
Bahman, Amir Sajjad; Ma, Ke; Blaabjerg, Frede
2016-01-01
Accurate thermal dynamics modeling of high power Insulated Gate Bipolar Transistor (IGBT) modules is important information for the reliability analysis and thermal design of power electronic systems. However, the existing thermal models have their limits to correctly predict these complicated...... thermal behaviors in the IGBTs. In this paper, a new three-dimensional (3D) lumped thermal model is proposed, which can easily be characterized from Finite Element Methods (FEM) based simulation and acquire the thermal distribution in critical points. Meanwhile the boundary conditions including...... the cooling system and power losses are modeled in the 3D thermal model, which can be adapted to different real field applications of power electronic converters. The accuracy of the proposed thermal model is verified by experimental results....
CSIR Research Space (South Africa)
Bernhardi, EH
2008-01-01
Full Text Available that determines the temperature and the thermally induced stresses in isotropic rods is presented. Even though the model is developed for isotropic rods, it is shown that it can also be used to accurately estimate the thermal effects in anisotropic rods...
Numerically modeling Brownian thermal noise in amorphous and crystalline thin coatings
Lovelace, Geoffrey; Demos, Nicholas; Khan, Haroon
2018-01-01
Thermal noise is expected to be one of the noise sources limiting the astrophysical reach of Advanced LIGO (once commissioning is complete) and third-generation detectors. Adopting crystalline materials for thin, reflecting mirror coatings, rather than the amorphous coatings used in current-generation detectors, could potentially reduce thermal noise. Understanding and reducing thermal noise requires accurate theoretical models, but modeling thermal noise analytically is especially challenging with crystalline materials. Thermal noise models typically rely on the fluctuation-dissipation theorem, which relates the power spectral density of the thermal noise to an auxiliary elastic problem. In this paper, we present results from a new, open-source tool that numerically solves the auxiliary elastic problem to compute the Brownian thermal noise for both amorphous and crystalline coatings. We employ the open-source deal.ii and PETSc frameworks to solve the auxiliary elastic problem using a finite-element method, adaptive mesh refinement, and parallel processing that enables us to use high resolutions capable of resolving the thin reflective coating. We verify numerical convergence, and by running on up to hundreds of compute cores, we resolve the coating elastic energy in the auxiliary problem to approximately 0.1%. We compare with approximate analytic solutions for amorphous materials, and we verify that our solutions scale as expected with changing beam size, mirror dimensions, and coating thickness. Finally, we model the crystalline coating thermal noise in an experiment reported by Cole et al (2013 Nat. Photon. 7 644–50), comparing our results to a simpler numerical calculation that treats the coating as an ‘effectively amorphous’ material. We find that treating the coating as a cubic crystal instead of as an effectively amorphous material increases the thermal noise by about 3%. Our results are a step toward better understanding and reducing thermal noise to
Thermal modelling. Preliminary site description Laxemar subarea - version 1.2
Energy Technology Data Exchange (ETDEWEB)
Sundberg, Jan; Wrafter, John; Back, Paer-Erik; Laendell, Maerta [Geo Innova AB, Linkoeping (Sweden)
2006-02-15
This report presents the thermal site descriptive model for the Laxemar subarea, version 1.2. The main objective of this report is to present the thermal modelling work where data has been identified, quality controlled, evaluated and summarised in order to make an upscaling to lithological domain level possible. The thermal conductivity at canister scale has been modelled for five different lithological domains: RSMA (Aevroe granite), RSMBA (mixture of Aevroe granite and fine-grained dioritoid), RSMD (quartz monzodiorite), RSME (diorite/gabbro) and RSMM (mix domain with high frequency of diorite to gabbro). A base modelling approach has been used to determine the mean value of the thermal conductivity. Four alternative/complementary approaches have been used to evaluate the spatial variability of the thermal conductivity at domain level. The thermal modelling approaches are based on the lithological domain model for the Laxemar subarea, version 1.2 together with rock type models based on measured and calculated (from mineral composition) thermal conductivities. For one rock type, Aevroe granite (501044), density loggings have also been used in the domain modelling in order to evaluate the spatial variability within the Aevroe granite. This has been possible due to an established relationship between density and thermal conductivity, valid for the Aevroe granite. Results indicate that the means of thermal conductivity for the various domains are expected to exhibit a variation from 2.45 W/(m.K) to 2.87 W/(m.K). The standard deviation varies according to the scale considered, and for the 0.8 m scale it is expected to range from 0.17 to 0.29 W/(m.K). Estimates of lower tail percentiles for the same scale are presented for all five domains. The temperature dependence is rather small with a decrease in thermal conductivity of 1.1-5.3% per 100 deg C increase in temperature for the dominant rock types. There are a number of important uncertainties associated with these
Spatial-temporal modeling of malware propagation in networks.
Chen, Zesheng; Ji, Chuanyi
2005-09-01
Network security is an important task of network management. One threat to network security is malware (malicious software) propagation. One type of malware is called topological scanning that spreads based on topology information. The focus of this work is on modeling the spread of topological malwares, which is important for understanding their potential damages, and for developing countermeasures to protect the network infrastructure. Our model is motivated by probabilistic graphs, which have been widely investigated in machine learning. We first use a graphical representation to abstract the propagation of malwares that employ different scanning methods. We then use a spatial-temporal random process to describe the statistical dependence of malware propagation in arbitrary topologies. As the spatial dependence is particularly difficult to characterize, the problem becomes how to use simple (i.e., biased) models to approximate the spatially dependent process. In particular, we propose the independent model and the Markov model as simple approximations. We conduct both theoretical analysis and extensive simulations on large networks using both real measurements and synthesized topologies to test the performance of the proposed models. Our results show that the independent model can capture temporal dependence and detailed topology information and, thus, outperforms the previous models, whereas the Markov model incorporates a certain spatial dependence and, thus, achieves a greater accuracy in characterizing both transient and equilibrium behaviors of malware propagation.
Flood routing modelling with Artificial Neural Networks
Directory of Open Access Journals (Sweden)
R. Peters
2006-01-01
Full Text Available For the modelling of the flood routing in the lower reaches of the Freiberger Mulde river and its tributaries the one-dimensional hydrodynamic modelling system HEC-RAS has been applied. Furthermore, this model was used to generate a database to train multilayer feedforward networks. To guarantee numerical stability for the hydrodynamic modelling of some 60 km of streamcourse an adequate resolution in space requires very small calculation time steps, which are some two orders of magnitude smaller than the input data resolution. This leads to quite high computation requirements seriously restricting the application – especially when dealing with real time operations such as online flood forecasting. In order to solve this problem we tested the application of Artificial Neural Networks (ANN. First studies show the ability of adequately trained multilayer feedforward networks (MLFN to reproduce the model performance.
International Nuclear Information System (INIS)
Yarlagadda, B.S.
1989-04-01
The three-dimensional thermal hydraulics computer code COMMIX-1AR was used to analyze four constant flow thermal upramp experiments performed in the thermal hydraulic model of an advanced LMR. An objective of these analyses was the validation of COMMIX-1AR for buoyancy affected flows. The COMMIX calculated temperature histories of some thermocouples in the model were compared with the corresponding measured data. The conclusions of this work are presented. 3 refs., 5 figs
Absence of local thermal equilibrium in two models of heat conduction
Dhar, Abhishek; Dhar, Deepak
1998-01-01
A crucial assumption in the conventional description of thermal conduction is the existence of local thermal equilibrium. We test this assumption in two simple models of heat conduction. Our first model is a linear chain of planar spins with nearest neighbour couplings, and the second model is that of a Lorentz gas. We look at the steady state of the system when the two ends are connected to heat baths at temperatures T1 and T2. If T1=T2, the system reaches thermal equilibrium. If T1 is not e...
An evolving network model with modular growth
International Nuclear Information System (INIS)
Zou Zhi-Yun; Liu Peng; Lei Li; Gao Jian-Zhi
2012-01-01
In this paper, we propose an evolving network model growing fast in units of module, according to the analysis of the evolution characteristics in real complex networks. Each module is a small-world network containing several interconnected nodes and the nodes between the modules are linked by preferential attachment on degree of nodes. We study the modularity measure of the proposed model, which can be adjusted by changing the ratio of the number of inner-module edges and the number of inter-module edges. In view of the mean-field theory, we develop an analytical function of the degree distribution, which is verified by a numerical example and indicates that the degree distribution shows characteristics of the small-world network and the scale-free network distinctly at different segments. The clustering coefficient and the average path length of the network are simulated numerically, indicating that the network shows the small-world property and is affected little by the randomness of the new module. (interdisciplinary physics and related areas of science and technology)
Thermal modelling. Preliminary site description Simpevarp subarea - version 1.2
International Nuclear Information System (INIS)
Sundberg, Jan; Back, Paer-Erik; Bengtsson, Anna; Laendell, Maerta
2005-08-01
This report presents the thermal site descriptive model for the Simpevarp subarea, version 1.2. The main objective of this report is to present the thermal modelling work where data has been identified, quality controlled, evaluated and summarised in order to make an upscaling to lithological domain level possible. The thermal conductivity at possible canister scale has been modelled for four different lithological domains (RSMA01 (Aevroe granite), RSMB01 (Fine-grained dioritoid), RSMC01 (mixture of Aevroe granite and Quartz monzodiorite), and RSMD01 (Quartz monzodiorite)). A main modelling approach has been used to determine the mean value of the thermal conductivity. Three alternative/complementary approaches have been used to evaluate the spatial variability of the thermal conductivity at domain level. The thermal modelling approaches are based on the lithological model for the Simpevarp subarea, version 1.2 together with rock type models constituted from measured and calculated (from mineral composition) thermal conductivities. For one rock type, the Aevroe granite (501044), density loggings within the specific rock type has also been used in the domain modelling in order to consider the spatial variability within the Aevroe granite. This has been possible due to the presented relationship between density and thermal conductivity, valid for the Aevroe granite. Results indicate that the mean of thermal conductivity is expected to exhibit only a small variation between the different domains, from 2.62 W/(m.K) to 2.80 W/(m.K). The standard deviation varies according to the scale considered and for the canister scale it is expected to range from 0.20 to 0.28 W/(m.K). Consequently, the lower confidence limit (95% confidence) for the canister scale is within the range 2.04-2.35 W/(m.K) for the different domains. The temperature dependence is rather small with a decrease in thermal conductivity of 1.1-3.4% per 100 deg C increase in temperature for the dominating rock
Directory of Open Access Journals (Sweden)
Wang Hao
2016-01-01
Full Text Available In current communication network for distribution in Chinese power grid systems, the fiber communication backbone network for distribution and TD-LTE power private wireless backhaul network of power grid are both bearing by the SDH optical transmission network, which also carries the communication network of transformer substation and main electric. As the data traffic of the distribution communication and TD-LTE power private wireless network grow rapidly in recent years, it will have a big impact with the SDH network’s bearing capacity which is mainly used for main electric communication in high security level. This paper presents a fusion networking model which use a multiple-layer PTN network as the unified bearing of the TD-LTE power private wireless backhaul network and fiber communication backbone network for distribution. Network dataflow analysis shows that this model can greatly reduce the capacity pressure of the traditional SDH network as well as ensure the reliability of the transmission of the communication network for distribution and TD-LTE power private wireless network.
UAV Trajectory Modeling Using Neural Networks
Xue, Min
2017-01-01
Massive small unmanned aerial vehicles are envisioned to operate in the near future. While there are lots of research problems need to be addressed before dense operations can happen, trajectory modeling remains as one of the keys to understand and develop policies, regulations, and requirements for safe and efficient unmanned aerial vehicle operations. The fidelity requirement of a small unmanned vehicle trajectory model is high because these vehicles are sensitive to winds due to their small size and low operational altitude. Both vehicle control systems and dynamic models are needed for trajectory modeling, which makes the modeling a great challenge, especially considering the fact that manufactures are not willing to share their control systems. This work proposed to use a neural network approach for modelling small unmanned vehicle's trajectory without knowing its control system and bypassing exhaustive efforts for aerodynamic parameter identification. As a proof of concept, instead of collecting data from flight tests, this work used the trajectory data generated by a mathematical vehicle model for training and testing the neural network. The results showed great promise because the trained neural network can predict 4D trajectories accurately, and prediction errors were less than 2:0 meters in both temporal and spatial dimensions.
Modeling Evolution on Nearly Neutral Network Fitness Landscapes
Yakushkina, Tatiana; Saakian, David B.
2017-08-01
To describe virus evolution, it is necessary to define a fitness landscape. In this article, we consider the microscopic models with the advanced version of neutral network fitness landscapes. In this problem setting, we suppose a fitness difference between one-point mutation neighbors to be small. We construct a modification of the Wright-Fisher model, which is related to ordinary infinite population models with nearly neutral network fitness landscape at the large population limit. From the microscopic models in the realistic sequence space, we derive two versions of nearly neutral network models: with sinks and without sinks. We claim that the suggested model describes the evolutionary dynamics of RNA viruses better than the traditional Wright-Fisher model with few sequences.
Thermal modelling of Advanced LIGO test masses
International Nuclear Information System (INIS)
Wang, H; Dovale Álvarez, M; Mow-Lowry, C M; Freise, A; Blair, C; Brooks, A; Kasprzack, M F; Ramette, J; Meyers, P M; Kaufer, S; O’Reilly, B
2017-01-01
High-reflectivity fused silica mirrors are at the epicentre of today’s advanced gravitational wave detectors. In these detectors, the mirrors interact with high power laser beams. As a result of finite absorption in the high reflectivity coatings the mirrors suffer from a variety of thermal effects that impact on the detectors’ performance. We propose a model of the Advanced LIGO mirrors that introduces an empirical term to account for the radiative heat transfer between the mirror and its surroundings. The mechanical mode frequency is used as a probe for the overall temperature of the mirror. The thermal transient after power build-up in the optical cavities is used to refine and test the model. The model provides a coating absorption estimate of 1.5–2.0 ppm and estimates that 0.3 to 1.3 ppm of the circulating light is scattered onto the ring heater. (paper)
Sommer, W.T.
2015-01-01
Modelling and monitoring of Aquifer Thermal Energy Storage
Impacts of heterogeneity, thermal interference and bioremediation
Wijbrand Sommer
PhD thesis, Wageningen University, Wageningen, NL (2015)
ISBN 978-94-6257-294-2
Abstract
Aquifer
Model for the growth of the world airline network
Verma, T.; Araújo, N. A. M.; Nagler, J.; Andrade, J. S.; Herrmann, H. J.
2016-06-01
We propose a probabilistic growth model for transport networks which employs a balance between popularity of nodes and the physical distance between nodes. By comparing the degree of each node in the model network and the World Airline Network (WAN), we observe that the difference between the two is minimized for α≈2. Interestingly, this is the value obtained for the node-node correlation function in the WAN. This suggests that our model explains quite well the growth of airline networks.
Security Modeling on the Supply Chain Networks
Directory of Open Access Journals (Sweden)
Marn-Ling Shing
2007-10-01
Full Text Available In order to keep the price down, a purchaser sends out the request for quotation to a group of suppliers in a supply chain network. The purchaser will then choose a supplier with the best combination of price and quality. A potential supplier will try to collect the related information about other suppliers so he/she can offer the best bid to the purchaser. Therefore, confidentiality becomes an important consideration for the design of a supply chain network. Chen et al. have proposed the application of the Bell-LaPadula model in the design of a secured supply chain network. In the Bell-LaPadula model, a subject can be in one of different security clearances and an object can be in one of various security classifications. All the possible combinations of (Security Clearance, Classification pair in the Bell-LaPadula model can be thought as different states in the Markov Chain model. This paper extends the work done by Chen et al., provides more details on the Markov Chain model and illustrates how to use it to monitor the security state transition in the supply chain network.
Thermal mechanical stress modeling of GCtM seals
Energy Technology Data Exchange (ETDEWEB)
Dai, Steve Xunhu [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Chambers, Robert [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
2015-09-01
Finite-element thermal stress modeling at the glass-ceramic to metal (GCtM) interface was conducted assuming heterogeneous glass-ceramic microstructure. The glass-ceramics were treated as composites consisting of high expansion silica crystalline phases dispersed in a uniform residual glass. Interfacial stresses were examined for two types of glass-ceramics. One was designated as SL16 glass -ceramic, owing to its step-like thermal strain curve with an overall coefficient of thermal expansion (CTE) at 16 ppm/ºC. Clustered Cristobalite is the dominant silica phase in SL16 glass-ceramic. The other, designated as NL16 glass-ceramic, exhibited clusters of mixed Cristobalite and Quartz and showed a near-linear thermal strain curve with a same CTE value.
Modeling the propagation of mobile malware on complex networks
Liu, Wanping; Liu, Chao; Yang, Zheng; Liu, Xiaoyang; Zhang, Yihao; Wei, Zuxue
2016-08-01
In this paper, the spreading behavior of malware across mobile devices is addressed. By introducing complex networks to model mobile networks, which follows the power-law degree distribution, a novel epidemic model for mobile malware propagation is proposed. The spreading threshold that guarantees the dynamics of the model is calculated. Theoretically, the asymptotic stability of the malware-free equilibrium is confirmed when the threshold is below the unity, and the global stability is further proved under some sufficient conditions. The influences of different model parameters as well as the network topology on malware propagation are also analyzed. Our theoretical studies and numerical simulations show that networks with higher heterogeneity conduce to the diffusion of malware, and complex networks with lower power-law exponents benefit malware spreading.
Quebec mental health services networks: models and implementation
Directory of Open Access Journals (Sweden)
Marie-Josée Fleury
2005-06-01
Full Text Available Purpose: In the transformation of health care systems, the introduction of integrated service networks is considered to be one of the main solutions for enhancing efficiency. In the last few years, a wealth of literature has emerged on the topic of services integration. However, the question of how integrated service networks should be modelled to suit different implementation contexts has barely been touched. To fill that gap, this article presents four models for the organization of mental health integrated networks. Data sources: The proposed models are drawn from three recently published studies on mental health integrated services in the province of Quebec (Canada with the author as principal investigator. Description: Following an explanation of the concept of integrated service network and a description of the Quebec context for mental health networks, the models, applicable in all settings: rural, urban or semi-urban, and metropolitan, and summarized in four figures, are presented. Discussion and conclusion: To apply the models successfully, the necessity of rallying all the actors of a system, from the strategic, tactical and operational levels, according to the type of integration involved: functional/administrative, clinical and physician-system is highlighted. The importance of formalizing activities among organizations and actors in a network and reinforcing the governing mechanisms at the local level is also underlined. Finally, a number of integration strategies and key conditions of success to operationalize integrated service networks are suggested.
Analytical thermal model validation for Cassini radioisotope thermoelectric generator
International Nuclear Information System (INIS)
Lin, E.I.
1997-01-01
The Saturn-bound Cassini spacecraft is designed to rely, without precedent, on the waste heat from its three radioisotope thermoelectric generators (RTGs) to warm the propulsion module subsystem, and the RTG end dome temperature is a key determining factor of the amount of waste heat delivered. A previously validated SINDA thermal model of the RTG was the sole guide to understanding its complex thermal behavior, but displayed large discrepancies against some initial thermal development test data. A careful revalidation effort led to significant modifications and adjustments of the model, which result in a doubling of the radiative heat transfer from the heat source support assemblies to the end domes and bring up the end dome and flange temperature predictions to within 2 C of the pertinent test data. The increased inboard end dome temperature has a considerable impact on thermal control of the spacecraft central body. The validation process offers an example of physically-driven analytical model calibration with test data from not only an electrical simulator but also a nuclear-fueled flight unit, and has established the end dome temperatures of a flight RTG where no in-flight or ground-test data existed before
An improved UO2 thermal conductivity model in the ELESTRES computer code
International Nuclear Information System (INIS)
Chassie, G.G.; Tochaie, M.; Xu, Z.
2010-01-01
This paper describes the improved UO 2 thermal conductivity model for use in the ELESTRES (ELEment Simulation and sTRESses) computer code. The ELESTRES computer code models the thermal, mechanical and microstructural behaviour of a CANDU® fuel element under normal operating conditions. The main purpose of the code is to calculate fuel temperatures, fission gas release, internal gas pressure, fuel pellet deformation, and fuel sheath strains for fuel element design and assessment. It is also used to provide initial conditions for evaluating fuel behaviour during high temperature transients. The thermal conductivity of UO 2 fuel is one of the key parameters that affect ELESTRES calculations. The existing ELESTRES thermal conductivity model has been assessed and improved based on a large amount of thermal conductivity data from measurements of irradiated and un-irradiated UO 2 fuel with different densities. The UO 2 thermal conductivity data cover 90% to 99% theoretical density of UO 2 , temperature up to 3027 K, and burnup up to 1224 MW·h/kg U. The improved thermal conductivity model, which is recommended for a full implementation in the ELESTRES computer code, has reduced the ELESTRES code prediction biases of temperature, fission gas release, and fuel sheath strains when compared with the available experimental data. This improved thermal conductivity model has also been checked with a test version of ELESTRES over the full ranges of fuel temperature, fuel burnup, and fuel density expected in CANDU fuel. (author)
Network Design Models for Container Shipping
DEFF Research Database (Denmark)
Reinhardt, Line Blander; Kallehauge, Brian; Nielsen, Anders Nørrelund
This paper presents a study of the network design problem in container shipping. The paper combines the network design and fleet assignment problem into a mixed integer linear programming model minimizing the overall cost. The major contributions of this paper is that the time of a vessel route...... is included in the calculation of the capacity and that a inhomogeneous fleet is modeled. The model also includes the cost of transshipment which is one of the major cost for the shipping companies. The concept of pseudo simple routes is introduced to expand the set of feasible routes. The linearization...
Dynamic Evolution Model Based on Social Network Services
Xiong, Xi; Gou, Zhi-Jian; Zhang, Shi-Bin; Zhao, Wen
2013-11-01
Based on the analysis of evolutionary characteristics of public opinion in social networking services (SNS), in the paper we propose a dynamic evolution model, in which opinions are coupled with topology. This model shows the clustering phenomenon of opinions in dynamic network evolution. The simulation results show that the model can fit the data from a social network site. The dynamic evolution of networks accelerates the opinion, separation and aggregation. The scale and the number of clusters are influenced by confidence limit and rewiring probability. Dynamic changes of the topology reduce the number of isolated nodes, while the increased confidence limit allows nodes to communicate more sufficiently. The two effects make the distribution of opinion more neutral. The dynamic evolution of networks generates central clusters with high connectivity and high betweenness, which make it difficult to control public opinions in SNS.
A growing social network model in geographical space
Antonioni, Alberto; Tomassini, Marco
2017-09-01
In this work we propose a new model for the generation of social networks that includes their often ignored spatial aspects. The model is a growing one and links are created either taking space into account, or disregarding space and only considering the degree of target nodes. These two effects can be mixed linearly in arbitrary proportions through a parameter. We numerically show that for a given range of the combination parameter, and for given mean degree, the generated network class shares many important statistical features with those observed in actual social networks, including the spatial dependence of connections. Moreover, we show that the model provides a good qualitative fit to some measured social networks.
Characterization and modeling of the thermal mechanics of lithium-ion battery cells
International Nuclear Information System (INIS)
Oh, Ki-Yong; Epureanu, Bogdan I.
2016-01-01
Highlights: • Thermal swelling shape is different than Li-ion intercalation swelling shape. • Nonuniform temperature and gap creation leads to a convex shape at free conditions. • Important parameters of thermal mechanics are estimated through experiments. • A coupled thermal-structural analysis accurately predicts thermal swelling shape. • Nonuniform temperature still plays a critical role at pack conditions. - Abstract: The thermal mechanics of Lithium-ion (Li-ion) batteries is explored with a focus on thermal swelling. Experiments show for the first time that the swelling shape of prismatic battery cells due to temperature variations is significantly different from that due to Li-ion intercalation in unconstrained conditions. In contrast to uniform and orthotropic Li-ion intercalation swelling in a direction perpendicular to electrodes, the nonuniform temperature distribution in the jellyroll and the gaps/voids between electrodes result in distinguishable different swelling shapes. A unique coupled thermal-structural analysis with a simple, but efficient 3-D finite numerical model is proposed to investigate the impact of temperature variations on the thermal behaviors of battery cells. Anisotropic heat conduction and temperature dependency of the coefficient of thermal expansion are taken into account and found to have an impact on temperature distribution and thermal expansion. Experimental validation of the proposed model clearly demonstrates that the coupled thermal-structural analysis with the proposed model can predict accurately the thermal swelling at unconstrained conditions. The solution at pack (constrained) conditions shows that the nonuniform temperature distribution of the jellyroll still plays a critical role for the thermal swelling shape, although the gaps/voids do not occur because of the constraints from spacers in the pack, suggesting that the estimation of core temperature is important. Such an accurate model, able to estimate cell
Directory of Open Access Journals (Sweden)
Coral Rodrigo
2015-03-01
Full Text Available This paper presents a new test method able to infer - in periods of less than 7 seconds - the refrigeration capacity of a compressor used in thermal machines, which represents a time reduction of approximately 99.95% related to the standardized traditional methods. The method was developed aiming at its application on compressor manufacture lines and on 100% of the units produced. Artificial neural networks (ANNs were used to establish a model able to infer the refrigeration capacity based on the data collected directly on the production line. The proposed method does not make use of refrigeration systems and also does not require using the compressor oil.
Thermal Model of a Dish Stirling Cavity-Receiver
Directory of Open Access Journals (Sweden)
Rubén Gil
2015-01-01
Full Text Available This paper presents a thermal model for a dish Stirling cavity based on the finite differences method. This model is a theoretical tool to optimize the cavity in terms of thermal efficiency. One of the main outcomes of this work is the evaluation of radiative exchange using the radiosity method; for that purpose, the view factors of all surfaces involved have been accurately calculated. Moreover, this model enables the variation of the cavity and receiver dimensions and the materials to determine the optimal cavity design. The tool has been used to study the cavity optimization regarding geometry parameters and material properties. Receiver absorptivity has been identified as the most influential property of the materials. The optimal aperture height depends on the minimum focal space.
Hybrid simulation models of production networks
Kouikoglou, Vassilis S
2001-01-01
This book is concerned with a most important area of industrial production, that of analysis and optimization of production lines and networks using discrete-event models and simulation. The book introduces a novel approach that combines analytic models and discrete-event simulation. Unlike conventional piece-by-piece simulation, this method observes a reduced number of events between which the evolution of the system is tracked analytically. Using this hybrid approach, several models are developed for the analysis of production lines and networks. The hybrid approach combines speed and accuracy for exceptional analysis of most practical situations. A number of optimization problems, involving buffer design, workforce planning, and production control, are solved through the use of hybrid models.
Network Modeling and Simulation A Practical Perspective
Guizani, Mohsen; Khan, Bilal
2010-01-01
Network Modeling and Simulation is a practical guide to using modeling and simulation to solve real-life problems. The authors give a comprehensive exposition of the core concepts in modeling and simulation, and then systematically address the many practical considerations faced by developers in modeling complex large-scale systems. The authors provide examples from computer and telecommunication networks and use these to illustrate the process of mapping generic simulation concepts to domain-specific problems in different industries and disciplines. Key features: Provides the tools and strate
Performance modeling, stochastic networks, and statistical multiplexing
Mazumdar, Ravi R
2013-01-01
This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of introducing an appropriate mathematical framework for modeling and analysis as well as understanding the phenomenon of statistical multiplexing. The models, techniques, and results presented form the core of traffic engineering methods used to design, control and allocate resources in communication networks.The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the importan
CFD modeling of thermal mixing in a T-junction geometry using LES model
Energy Technology Data Exchange (ETDEWEB)
Ayhan, Hueseyin, E-mail: huseyinayhan@hacettepe.edu.tr [Hacettepe University, Department of Nuclear Engineering, Beytepe, Ankara 06800 (Turkey); Soekmen, Cemal Niyazi, E-mail: cemalniyazi.sokmen@hacettepe.edu.tr [Hacettepe University, Department of Nuclear Engineering, Beytepe, Ankara 06800 (Turkey)
2012-12-15
Highlights: Black-Right-Pointing-Pointer CFD simulations of temperature and velocity fluctuations for thermal mixing cases in T-junction are performed. Black-Right-Pointing-Pointer It is found that the frequency range of 2-5 Hz contains most of the energy; therefore, may cause thermal fatigue. Black-Right-Pointing-Pointer This study shows that RANS based calculations fail to predict a realistic mixing between the fluids. Black-Right-Pointing-Pointer LES model can predict instantaneous turbulence behavior. - Abstract: Turbulent mixing of fluids at different temperatures can lead to temperature fluctuations at the pipe material. These fluctuations, or thermal striping, inducing cyclical thermal stresses and resulting thermal fatigue, may cause unexpected failure of pipe material. Therefore, an accurate characterization of temperature fluctuations is important in order to estimate the lifetime of pipe material. Thermal fatigue of the coolant circuits of nuclear power plants is one of the major issues in nuclear safety. To investigate thermal fatigue damage, the OECD/NEA has recently organized a blind benchmark study including some of results of present work for prediction of temperature and velocity fluctuations performing a thermal mixing experiment in a T-junction. This paper aims to estimate the frequency of velocity and temperature fluctuations in the mixing region using Computational Fluid Dynamics (CFD). Reynolds Averaged Navier-Stokes and Large Eddy Simulation (LES) models were used to simulate turbulence. CFD results were compared with the available experimental results. Predicted LES results, even in coarse mesh, were found to be in well-agreement with the experimental results in terms of amplitude and frequency of temperature and velocity fluctuations. Analysis of the temperature fluctuations and the power spectrum densities (PSD) at the locations having the strongest temperature fluctuations in the tee junction shows that the frequency range of 2-5 Hz
Switching performance of OBS network model under prefetched real traffic
Huang, Zhenhua; Xu, Du; Lei, Wen
2005-11-01
Optical Burst Switching (OBS) [1] is now widely considered as an efficient switching technique in building the next generation optical Internet .So it's very important to precisely evaluate the performance of the OBS network model. The performance of the OBS network model is variable in different condition, but the most important thing is that how it works under real traffic load. In the traditional simulation models, uniform traffics are usually generated by simulation software to imitate the data source of the edge node in the OBS network model, and through which the performance of the OBS network is evaluated. Unfortunately, without being simulated by real traffic, the traditional simulation models have several problems and their results are doubtable. To deal with this problem, we present a new simulation model for analysis and performance evaluation of the OBS network, which uses prefetched IP traffic to be data source of the OBS network model. The prefetched IP traffic can be considered as real IP source of the OBS edge node and the OBS network model has the same clock rate with a real OBS system. So it's easy to conclude that this model is closer to the real OBS system than the traditional ones. The simulation results also indicate that this model is more accurate to evaluate the performance of the OBS network system and the results of this model are closer to the actual situation.
Modeling and control of magnetorheological fluid dampers using neural networks
Wang, D. H.; Liao, W. H.
2005-02-01
Due to the inherent nonlinear nature of magnetorheological (MR) fluid dampers, one of the challenging aspects for utilizing these devices to achieve high system performance is the development of accurate models and control algorithms that can take advantage of their unique characteristics. In this paper, the direct identification and inverse dynamic modeling for MR fluid dampers using feedforward and recurrent neural networks are studied. The trained direct identification neural network model can be used to predict the damping force of the MR fluid damper on line, on the basis of the dynamic responses across the MR fluid damper and the command voltage, and the inverse dynamic neural network model can be used to generate the command voltage according to the desired damping force through supervised learning. The architectures and the learning methods of the dynamic neural network models and inverse neural network models for MR fluid dampers are presented, and some simulation results are discussed. Finally, the trained neural network models are applied to predict and control the damping force of the MR fluid damper. Moreover, validation methods for the neural network models developed are proposed and used to evaluate their performance. Validation results with different data sets indicate that the proposed direct identification dynamic model using the recurrent neural network can be used to predict the damping force accurately and the inverse identification dynamic model using the recurrent neural network can act as a damper controller to generate the command voltage when the MR fluid damper is used in a semi-active mode.
Analysis and logical modeling of biological signaling transduction networks
Sun, Zhongyao
The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.
UAV Trajectory Modeling Using Neural Networks
Xue, Min
2017-01-01
Large amount of small Unmanned Aerial Vehicles (sUAVs) are projected to operate in the near future. Potential sUAV applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. sUAVs are expected to operate in the uncontrolled Class G airspace, which is at or below 500 feet above ground level (AGL), where many static and dynamic constraints exist, such as ground properties and terrains, restricted areas, various winds, manned helicopters, and conflict avoidance among sUAVs. How to enable safe, efficient, and massive sUAV operations at the low altitude airspace remains a great challenge. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative works on establishing infrastructure and developing policies, requirement, and rules to enable safe and efficient sUAVs' operations. To achieve this goal, it is important to gain insights of future UTM traffic operations through simulations, where the accurate trajectory model plays an extremely important role. On the other hand, like what happens in current aviation development, trajectory modeling should also serve as the foundation for any advanced concepts and tools in UTM. Accurate models of sUAV dynamics and control systems are very important considering the requirement of the meter level precision in UTM operations. The vehicle dynamics are relatively easy to derive and model, however, vehicle control systems remain unknown as they are usually kept by manufactures as a part of intellectual properties. That brings challenges to trajectory modeling for sUAVs. How to model the vehicle's trajectories with unknown control system? This work proposes to use a neural network to model a vehicle's trajectory. The neural network is first trained to learn the vehicle's responses at numerous conditions. Once being fully trained, given current vehicle states, winds, and desired future trajectory, the neural
Electro-thermal characterization of Lithium Iron Phosphate cell with equivalent circuit modeling
International Nuclear Information System (INIS)
Saw, L.H.; Ye, Y.; Tay, A.A.O.
2014-01-01
Highlights: • We modeled the electrical and thermal behavior of the Li-ion battery. • We validated the simulation results with experimental studies. • We studied the thermal response of the battery pack using UDDS and US06 test. • Active cooling system is needed to prolong life cycle of cell. - Abstract: Prediction of the battery performance is important in the development of the electric vehicles battery pack. A battery model that is capable to reproduce I–V characteristic, thermal response and predicting the state of charge of the battery will benefit the development of cell and reduce time to market for electric vehicles. In this work, an equivalent circuit model coupled with the thermal model is used to analyze the electrical and thermal behavior of Lithium Iron Phosphate pouch cell under various operating conditions. The battery model is comprised three RC blocks, one series resistor and one voltage source. The parameters of the battery model are extracted from pulse discharge curve under different temperatures. The simulations results of the battery model under constant current discharge and pulse charge and discharge show a good agreement with experimental data. The validated battery model is then extended to investigate the dynamic behavior of the electric vehicle battery pack using UDDS and US06 test cycle. The simulation results show that an active thermal management system is required to prolong the calendar life and ensure safety of the battery pack
TRSM-a thermal-hydraulic real-time simulation model for PWR
International Nuclear Information System (INIS)
Zhou Weichang
1997-01-01
TRSM (a Thermal-hydraulic Real-time Simulation Model) has been developed for PWR real-time simulation and best-estimate prediction of normal operating and abnormal accident conditions. It is a non-equilibrium two phase flow thermal-hydraulic model based on five basic conservation equations. A drift flux model is used to account for the unequal velocities of liquid and gaseous mixture, with or without the presence of the noncondensibles. Critical flow models are applied for break flow and valve flow calculations. A 5-regime two phase heat convection model is applied for clad-to-coolant as well as fluid-to-tubing heat transfer. A rigorous reactor coolant pump model is used to calculate the pressure drop and rise for the suction and discharge ends with complete pump characteristics curves included. The TRSM model has been adapted in the full-scale training simulator of Qinshan Nuclear Power Plant 300 MW unit to simulate the thermal-hydraulic performance of the NSSS. The simulation results of a cold leg LOCA and a steam generator tube rupture (SGTR) accident are presented
Resistor-network anomalies in the heat transport of random harmonic chains.
Weinberg, Isaac; de Leeuw, Yaron; Kottos, Tsampikos; Cohen, Doron
2016-06-01
We consider thermal transport in low-dimensional disordered harmonic networks of coupled masses. Utilizing known results regarding Anderson localization, we derive the actual dependence of the thermal conductance G on the length L of the sample. This is required by nanotechnology implementations because for such networks Fourier's law G∝1/L^{α} with α=1 is violated. In particular we consider "glassy" disorder in the coupling constants and find an anomaly which is related by duality to the Lifshitz-tail regime in the standard Anderson model.
Thermal conductivity of Al–Cu–Mg–Si alloys: Experimental measurement and CALPHAD modeling
Energy Technology Data Exchange (ETDEWEB)
Zhang, Cong [State Key Laboratory of Powder Metallurgy, Central South University, Changsha, Hunan 410083 (China); Sino-German cooperation group “Microstructure in Al alloys”, Central South University, Changsha, Hunan 410083 (China); Du, Yong, E-mail: yong-du@csu.edu.cn [State Key Laboratory of Powder Metallurgy, Central South University, Changsha, Hunan 410083 (China); Sino-German cooperation group “Microstructure in Al alloys”, Central South University, Changsha, Hunan 410083 (China); Liu, Shuhong; Liu, Yuling [State Key Laboratory of Powder Metallurgy, Central South University, Changsha, Hunan 410083 (China); Sino-German cooperation group “Microstructure in Al alloys”, Central South University, Changsha, Hunan 410083 (China); Sundman, Bo. [INSTN, CEA Saclay, 91191 Gif-sur-Yvette Cedex (France)
2016-07-10
Highlights: • The thermal conductivities of Al–x wt% Cu (x = 1, 3, 5, 15 and 30) and Al–y wt% Si (y = 2, 12.5 and 20) alloys were determined. • The reported thermal conductivities of Al–Cu–Mg–Si system were critically reviewed. • The CALPHAD approach was applied for the modeling of thermal conductivity. • The applicability of CALPHAD technique in the modeling of thermal conductivity was discussed. - Abstract: In the present work, the thermal conductivities and microstructure of Al–x wt% Cu (x = 1, 3, 5, 15 and 30) and Al–y wt% Si (y = 2, 12.5 and 20) alloys were investigated by using laser-flash method, scanning electron microscopy (SEM) and X-ray diffraction (XRD). Besides, a CALPHAD (CALculation of PHAse Diagram) approach to evaluate the thermal conductivity of Al–Cu–Mg–Si system was performed. The numerical models for the thermal conductivity of pure elements and stoichiometric phases were described as polynomials, and the coefficients were optimized via PARROT module of Thermal-Calc software applied to the experimental data. The thermal conductivity of (Al)-based solid solutions was described by using Redlich–Kister interaction parameters. For alloys in two-phase region, the interface scattering parameter was proposed in the modeling to describe the impediment of interfaces on the heat transfer. Finally, a set of self-consistent parameters for the description of thermal conductivity in Al–Cu–Mg–Si system was obtained, and comprehensive comparisons between the calculated and measured thermal conductivities show that the experimental information is satisfactorily accounted for by the present modeling.
Microinstability-based model for anomalous thermal confinement in tokamaks
International Nuclear Information System (INIS)
Tang, W.M.
1986-03-01
This paper deals with the formulation of microinstability-based thermal transport coefficients (chi/sub j/) for the purpose of modelling anomalous energy confinement properties in tokamak plasmas. Attention is primarily focused on ohmically heated discharges and the associated anomalous electron thermal transport. An appropriate expression for chi/sub e/ is developed which is consistent with reasonable global constraints on the current and electron temperature profiles as well as with the key properties of the kinetic instabilities most likely to be present. Comparisons of confinement scaling trends predicted by this model with the empirical ohmic data base indicate quite favorable agreement. The subject of anomalous ion thermal transport and its implications for high density ohmic discharges and for auxiliary-heated plasmas is also addressed
Thermal conductivity of group-IV semiconductors from a kinetic-collective model.
de Tomas, C; Cantarero, A; Lopeandia, A F; Alvarez, F X
2014-09-08
The thermal conductivity of group-IV semiconductors (silicon, germanium, diamond and grey tin) with several isotopic compositions has been calculated from a kinetic-collective model. From this approach, significantly different to Callaway-like models in its physical interpretation, the thermal conductivity expression accounts for a transition from a kinetic (individual phonon transport) to a collective (hydrodynamic phonon transport) behaviour of the phonon field. Within the model, we confirm the theoretical proportionality between the phonon-phonon relaxation times of the group-IV semiconductors. This proportionality depends on some materials properties and it allows us to predict the thermal conductivity of the whole group of materials without the need to fit each material individually. The predictions on thermal conductivities are in good agreement with experimental data over a wide temperature range.
Thermal conductivity of group-IV semiconductors from a kinetic-collective model
de Tomas, C.; Cantarero, A.; Lopeandia, A. F.; Alvarez, F. X.
2014-01-01
The thermal conductivity of group-IV semiconductors (silicon, germanium, diamond and grey tin) with several isotopic compositions has been calculated from a kinetic-collective model. From this approach, significantly different to Callaway-like models in its physical interpretation, the thermal conductivity expression accounts for a transition from a kinetic (individual phonon transport) to a collective (hydrodynamic phonon transport) behaviour of the phonon field. Within the model, we confirm the theoretical proportionality between the phonon–phonon relaxation times of the group-IV semiconductors. This proportionality depends on some materials properties and it allows us to predict the thermal conductivity of the whole group of materials without the need to fit each material individually. The predictions on thermal conductivities are in good agreement with experimental data over a wide temperature range. PMID:25197256
International Nuclear Information System (INIS)
Sitprasert, Chatcharin; Dechaumphai, Pramote; Juntasaro, Varangrat
2009-01-01
The interfacial layer of nanoparticles has been recently shown to have an effect on the thermal conductivity of nanofluids. There is, however, still no thermal conductivity model that includes the effects of temperature and nanoparticle size variations on the thickness and consequently on the thermal conductivity of the interfacial layer. In the present work, the stationary model developed by Leong et al. (J Nanopart Res 8:245-254, 2006) is initially modified to include the thermal dispersion effect due to the Brownian motion of nanoparticles. This model is called the 'Leong et al.'s dynamic model'. However, the Leong et al.'s dynamic model over-predicts the thermal conductivity of nanofluids in the case of the flowing fluid. This suggests that the enhancement in the thermal conductivity of the flowing nanofluids due to the increase in temperature does not come from the thermal dispersion effect. It is more likely that the enhancement in heat transfer of the flowing nanofluids comes from the temperature-dependent interfacial layer effect. Therefore, the Leong et al.'s stationary model is again modified to include the effect of temperature variation on the thermal conductivity of the interfacial layer for different sizes of nanoparticles. This present model is then evaluated and compared with the other thermal conductivity models for the turbulent convective heat transfer in nanofluids along a uniformly heated tube. The results show that the present model is more general than the other models in the sense that it can predict both the temperature and the volume fraction dependence of the thermal conductivity of nanofluids for both non-flowing and flowing fluids. Also, it is found to be more accurate than the other models due to the inclusion of the effect of the temperature-dependent interfacial layer. In conclusion, the present model can accurately predict the changes in thermal conductivity of nanofluids due to the changes in volume fraction and temperature for
Modeling GMPLS and Optical MPLS Networks
DEFF Research Database (Denmark)
Christiansen, Henrik Lehrmann; Wessing, Henrik
2003-01-01
. The MPLS concept is attractive because it can work as a unifying control structure. covering all technologies. This paper describes how a novel scheme for optical MPLS and circuit switched GMPLS based networks can incorporated in such multi-domain, MPLS-based scenarios and how it could be modeled. Network...
Thermal Hydraulic design parameters study for severe accidents using neural networks
Energy Technology Data Exchange (ETDEWEB)
Roh, Chang Hyun; Chang, Soon Heung [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of); Chang, Keun Sun [Sunmoon University, Asan (Korea, Republic of)
1998-12-31
To provide the information on severe accident progression is very important for advanced or new type of nuclear power plant (NPP) design. A parametric study, therefore, was performed to investigate the effect of thermal hydraulic design parameters on severe accident progression of pressurized water reactors (PWRs). Nine parameters, which are considered important in NPP design or severe accident progression, were selected among the various thermal hydraulic design parameters. The backpropagation neural network (BPN) was used to determine parameters, which might more strongly affect the severe accident progression, among nine parameters. For training, different input patterns were generated by the latin hypercube sampling (LHS) technique and then different target patterns that contain core uncovery time and vessel failure time were obtained for Young Gwang Nuclear (YGN) Units 3 and 4 using modular accident analysis program (MAAP) 3.0B code. Three different severe accident scenarios, such as two loss of coolant accidents (LOCAs) and station blackout (SBO), were considered in this analysis. Results indicated that design parameters related to refueling water storage tank (RWST), accumulator and steam generator (S/G) have more dominant effects on the progression of severe accidents investigated, compared to the other six parameters. 9 refs., 5 tabs. (Author)
Thermal Hydraulic design parameters study for severe accidents using neural networks
Energy Technology Data Exchange (ETDEWEB)
Roh, Chang Hyun; Chang, Soon Heung [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of); Chang, Keun Sun [Sunmoon University, Asan (Korea, Republic of)
1997-12-31
To provide the information on severe accident progression is very important for advanced or new type of nuclear power plant (NPP) design. A parametric study, therefore, was performed to investigate the effect of thermal hydraulic design parameters on severe accident pro