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Journal articles on the topic 'Thermal network model'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Hijazi, Alaa, Paul Kreczanik, Eric Bideaux, Pascal Venet, Guy Clerc, and Michael Di Loreto. "Thermal Network Model of Supercapacitors Stack." IEEE Transactions on Industrial Electronics 59, no. 2 (2012): 979–87. http://dx.doi.org/10.1109/tie.2011.2158769.

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Azizian, Davood, and Mehdi Bigdeli. "A new cast-resin transformer thermal model based on recurrent neural networks." Archives of Electrical Engineering 66, no. 1 (2017): 17–28. http://dx.doi.org/10.1515/aee-2017-0002.

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Abstract Thermal modeling in the transient condition is very important for cast-resin dry-type transformers. In the present research, two novel dynamic thermal models have been introduced for the cast-resin dry-type transformer. These models are based on two artificial neural networks: the Elman recurrent networks (ELRN) and the nonlinear autoregressive model process with exogenous input (NARX). Using the experimental data, the introduced neural network thermal models have been trained. By selecting a typical transformer, the trained thermal models are validated using additional experimental r

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Guo, Qian Jian, and X. N. Qi. "Research on Thermal Error Modeling of NC Machine Tool Based on BP Neural Networks." Materials Science Forum 626-627 (August 2009): 135–40. http://dx.doi.org/10.4028/www.scientific.net/msf.626-627.135.

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Through analysis of the thermal errors affected NC machine tool, a new prediction model based on BP neural networks is presented, and ant colony algorithm is applied to train the weights of neural network model. Finally, thermal error compensation experiment is implemented, and the thermal error is reduced from 35μm to 6μm. The result shows that the local minimum problem of BP neural network is overcome, and the model accuracy is improved.

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Li, Ming, and Jin Ye. "Fractional Order Modeling of Thermal Circuits for an Integrated Energy System Based on Natural Transformation." Electronics 11, no. 6 (2022): 914. http://dx.doi.org/10.3390/electronics11060914.

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With the development of the economy, energy systems have become the focus of academia and industry. The integrated energy system formed by electricity, gas, and heat networks can improve the utilization efficiency of energy. Heating networks in integrated energy systems play an important role. The consideration of the dynamic characteristics of the heating network can improve the flexibility of the system and reduce the operation cost of the system. In this paper, a thermal circuit model is derived for the heating network from an electrical-analog perspective. Based on the thermal circuit mode

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5

Pozevalkin, V. V., and A. N. Polyakov. "Application of the digital model thermal errors of machine tools in automated production." Journal of Physics: Conference Series 2094, no. 4 (2021): 042022. http://dx.doi.org/10.1088/1742-6596/2094/4/042022.

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Abstract The article presents a predicting method for a machine tool thermal error based on a nonlinear autoregressive neural network with an external input, as well as methods for smoothing experimental data obtained from measuring devices by approximation using polynomial regression and the gray systems theory. The development of accurate and robust thermal models is a critical step in achieving high productivity in thermal deformation reduction techniques on machine tools. Because thermal deformations of the machine structure caused by temperature increase often lead to thermal errors and r

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Kim, Kwanyong, Seong Jun Yoon, and Woo Young Choi. "Dual random circuit breaker network model with equivalent thermal circuit network." Applied Physics Express 7, no. 2 (2014): 024203. http://dx.doi.org/10.7567/apex.7.024203.

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7

Alharbi, Ali Y., Deborah V. Pence, and Rebecca N. Cullion. "Thermal Characteristics of Microscale Fractal-Like Branching Channels." Journal of Heat Transfer 126, no. 5 (2004): 744–52. http://dx.doi.org/10.1115/1.1795236.

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Heat transfer through a fractal-like branching flow network is investigated using a three-dimensional computational fluid dynamics approach. Results are used for the purpose of assessing the validity of, and providing insight for improving, assumptions imposed in a previously developed one-dimensional model for predicting wall temperature distributions through fractal-like flow networks. As currently modeled, the one-dimensional code fairly well predicts the general wall temperature trend simulated by the three-dimensional model; hence, demonstrating its suitability as a tool for design of fra

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8

Wang, Pengyuan, Xinjian Wang, and Yunpeng Wang. "End-to-End Differentiable Physics Temperature Estimation for Permanent Magnet Synchronous Motor." World Electric Vehicle Journal 15, no. 4 (2024): 174. http://dx.doi.org/10.3390/wevj15040174.

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Differentiable physics is an approach that effectively combines physical models with deep learning, providing valuable information about physical systems during the training process of neural networks. This integration enhances the generalization ability and ensures better consistency with physical principles. In this work, we propose a framework for estimating the temperature of a permanent magnet synchronous motor by combining neural networks with the differentiable physical thermal model, as well as utilizing the simulation results. In detail, we first implement a differentiable thermal mod

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9

Gerstenmaier, Y. C., H. Pape, and G. Wachutka. "Rigorous model and network for static thermal problems." Microelectronics Journal 33, no. 9 (2002): 711–18. http://dx.doi.org/10.1016/s0026-2692(02)00054-x.

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10

Gerstenmaier, Y. C., and G. Wachutka. "Rigorous model and network for transient thermal problems." Microelectronics Journal 33, no. 9 (2002): 719–25. http://dx.doi.org/10.1016/s0026-2692(02)00055-1.

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11

Völzel, Constantin, and Stefan Lechner. "Grid-Coupled Geothermal and Decentralised Heat Supply Systems in a Holistic Open-Source Simulation Model for 5GDHC Networks." Sustainability 16, no. 23 (2024): 10503. https://doi.org/10.3390/su162310503.

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In order to reach climate protection goals at national or international levels, new forms of combined heating and cooling networks with ultra-low network temperatures (5GDHC) are viable alternatives to conventional heating networks. This paper presents a simulation library for 5GDHC networks as sustainable shared energy systems, developed in the object-oriented simulation framework OpenModelica. It comprises sub-models for residential buildings acting as prosumers in the network, with additional roof-mounted thermal systems, dynamic thermo-hydraulic representations of distribution pipes and st

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12

Liu, Zi Jian, Zhi Min Yu, Si Ming Li, and Yan Di Ai. "Application and Study of Fuzzy Neural Network Theory Based on Takagi-Sugeno Model to Thermal Error Modeling on NC Machine Tool." Advanced Materials Research 744 (August 2013): 147–52. http://dx.doi.org/10.4028/www.scientific.net/amr.744.147.

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For the degree of thermal deformation nonlinear is high and difficult to predict, fuzzy neural network modeling (FNN) based on Takagi-Sugeno model was applied to the NC machine tool thermal error modeling thus the complete thermal error fuzzy neural network mathematical model on NC machine tool was established and network parameters initialization and learning method were discussed. Thermal error experiment was conducted on large NC gantry rail grinder spindle box system and two independent groups of spindle thermal error data were collected, one was used to establish thermal error fuzzy neura

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13

Fukunaga, Shuhei, and Tsuyoshi Funaki. "Identification of High Resolution Transient Thermal Network Model for Power Module Packages." Materials Science Forum 1062 (May 31, 2022): 253–57. http://dx.doi.org/10.4028/p-90gl36.

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A transient thermal network model is utilized to design and evaluate the transient thermal characteristics of power modules. Static test method identifies the transient thermal network model from the time response of the junction temperature, which is obtained by using the temperature dependency of I-V characteristics for power devices. This paper experimentally evaluates the effect of the sampling frequency and the resolution of the AD conversion on the accuracy of the obtained transient thermal network model. The high sampling frequency and the high resolution in the obtained time response o

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14

Wang, Yang, Chaoyi Peng, and Weihua Zhang. "Network model for thermal conductivities of unidirectional fiber-reinforced composites." Materials Science-Poland 32, no. 4 (2014): 533–40. http://dx.doi.org/10.2478/s13536-014-0245-6.

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AbstractAn empirical network model has been developed to predict the in-plane thermal conductivities along arbitrary directions for unidirectional fiber-reinforced composites lamina. Measurements of thermal conductivities along different orientations were carried out. Good agreement was observed between values predicted by the network model and the experimental data; compared with the established analytical models, the newly proposed network model could give values with higher precision. Therefore, this network model is helpful to get a wider and more comprehensive understanding of heat transm

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15

Ma, Fuqiang, Feng Wang, Sheng Wang, Xianglin Li, and Yuan Li. "Rapid Coupling Analysis Model of Thermal Protection and Thermal Control for Electronic Equipment Cabin of High Speed Vehicles." Journal of Physics: Conference Series 2891, no. 11 (2024): 112022. https://doi.org/10.1088/1742-6596/2891/11/112022.

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Abstract In view of the serious problem of aerothermal “penetration” effect and equipment thermal accumulation effect in the electronic equipment cabin under long endurance and high speed flight conditions, this paper establishes thermal network models for thermal protection analysis and thermal control analysis based on lumped parameter principle, and verifies the validity of the thermal network models. Combined with thermal protection analysis model and thermal control analysis model, the thermal network model for coupling analysis of thermal protection and thermal control of electronic equi

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Kumar, Satish, Muhammad A. Alam, and Jayathi Y. Murthy. "Computational Model for Transport in Nanotube-Based Composites With Applications to Flexible Electronics." Journal of Heat Transfer 129, no. 4 (2006): 500–508. http://dx.doi.org/10.1115/1.2709969.

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Thermal and electrical transport in a new class of nanocomposites composed of random isotropic two-dimensional ensembles of nanotubes or nanowires in a substrate (host matrix) is considered for use in the channel region of thin-film transistors (TFTs). The random ensemble of nanotubes is generated numerically and each nanotube is discretized using a finite volume scheme. To simulate transport in composites, the network is embedded in a background substrate mesh, which is also discretized using a finite volume scheme. Energy and charge exchange between nanotubes at the points of contact and bet

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17

Lv, Yu Kun, Shuai Chang, Ze Kun Ge, and Wei Run Lv. "Research on Modeling Method of Thermodynamic Verifying Calculation for Heat-Supply Network." Advanced Materials Research 550-553 (July 2012): 2927–31. http://dx.doi.org/10.4028/www.scientific.net/amr.550-553.2927.

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This paper establishes a model of thermal checking calculation of heat supply network based on graph theory and thermodynamic calculation, by analyzing directly buried installation of thermal network utilizing the heat-transfer mechanism and principle of thermal equilibrium. Take the directly buried heat supply network for instance, in which hot water is as a heat medium. The establishment of the spatial database and attribute database of thermal network based on GIS and Microsoft Access respectively, as well as the thermodynamic calculation of thermal networks based on GIS developed by object

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18

An, Tong, Rui Zhou, Fei Qin, Yanwei Dai, Yanpeng Gong, and Pei Chen. "Comparative Study of the Parameter Acquisition Methods for the Cauer Thermal Network Model of an IGBT Module." Electronics 12, no. 7 (2023): 1650. http://dx.doi.org/10.3390/electronics12071650.

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Under the operating conditions of high power and high switching frequency, an insulated gate bipolar transistor (IGBT) chip can produce relatively large power loss, causing the junction temperature to rise rapidly; consequently, the reliability of the IGBT module can be seriously affected. Therefore, it is necessary to accurately predict the junction temperature of the IGBT chip. The resistance capacitance (RC) thermal network model is a commonly used method for IGBT junction temperature prediction. In this paper, the model parameters are obtained by two methods to establish the Cauer thermal

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19

Guo, Yujing, Ruihai Xu, and Xipeng Liu. "Research on accurate thermal network calculation model of modular permanent magnet motor." Journal of Physics: Conference Series 2418, no. 1 (2023): 012052. http://dx.doi.org/10.1088/1742-6596/2418/1/012052.

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Abstract This paper proposes a thermal network model for calculating the modular permanent magnet motor’s temperature rise. Analyzing the actual heat flow path of motor Joule loss and considering the circumferential heat conduction of winding, the local three-dimensional thermal network model of winding is constructed. Based on the model, the motor parts’ steady and dynamic temperature rise is calculated and verified by the FEM. The thermal network model also applies to motors with short winding ends and complex stator yokes.

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20

Wang, Jixin, Xiaoping Wang, Yongjiang Ma, Ning Liu, and Zhiyu Yang. "Analysis of Heat Transfer in Power Split Device for Hybrid Electric Vehicle Using Thermal Network Method." Advances in Mechanical Engineering 6 (January 1, 2014): 210170. http://dx.doi.org/10.1155/2014/210170.

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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, t

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21

Licklederer, Thomas, Daniel Zinsmeister, Ilya Elizarov, Vedran Perić, and Peter Tzscheutschler. "Characteristics and Challenges in Prosumer-Dominated Thermal Networks." Journal of Physics: Conference Series 2042, no. 1 (2021): 012039. http://dx.doi.org/10.1088/1742-6596/2042/1/012039.

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Abstract Prosumer-dominated thermal networks interconnect distributed prosumers. These networks form the infrastructure that allows to execute the trading of thermal energy as desired in the context of local energy markets. However, the significantly different behavior of such networks compared to conventional district heating and cooling networks has not yet been comprehensively investigated. This paper provides a compilation of instrinsic characteristics of prosumer-dominated thermal networks and discusses challenges that arise from these characteristics. As a basis for the investigations an

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22

Zhao, Songhan, Linlin Cai, Wangyong Chen, Yandong He, and Gang Du. "Self-Heating and Thermal Network Model for Complementary FET." IEEE Transactions on Electron Devices 69, no. 1 (2022): 11–16. http://dx.doi.org/10.1109/ted.2021.3130010.

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23

Fukunaga, Shuhei, and Tsuyoshi Funaki. "Transient thermal network model identification for power module packages." Nonlinear Theory and Its Applications, IEICE 11, no. 2 (2020): 157–69. http://dx.doi.org/10.1587/nolta.11.157.

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24

Cui, Haoyang, Fengye Hu, Yu Zhang, and Kun Zhou. "Heat spreading path optimization of IGBT thermal network model." Microelectronics Reliability 103 (December 2019): 113511. http://dx.doi.org/10.1016/j.microrel.2019.113511.

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25

Liu, Weiwei, Zhiwei Lian, and Bo Zhao. "A neural network evaluation model for individual thermal comfort." Energy and Buildings 39, no. 10 (2007): 1115–22. http://dx.doi.org/10.1016/j.enbuild.2006.12.005.

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26

Bodla, Karthik K., Jayathi Y. Murthy, and Suresh V. Garimella. "Resistance network-based thermal conductivity model for metal foams." Computational Materials Science 50, no. 2 (2010): 622–32. http://dx.doi.org/10.1016/j.commatsci.2010.09.026.

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27

Wu, Hao, Zhanfeng Ying, Zhihua Chen, and Wei Zu. "Establishment method of IGBT thermal network model based on electrothermal coupling simulation and parameter identification." Journal of Physics: Conference Series 2918, no. 1 (2024): 012028. https://doi.org/10.1088/1742-6596/2918/1/012028.

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Abstract To swiftly and precisely assess the IGBT’s thermal safety during the circuit design phase, this paper proposes a method of establishing an IGBT thermal network model by electrothermal coupling simulation and parameter identification. This model integrates electrothermal coupling simulation techniques and parameter identification methods. Firstly, the IGBT’s finite element model is established by COMSOL, aiming to acquire the temperature distribution patterns of the IGBT and its heat sink under various operating conditions. Then, the objective function of parameter identification is co

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28

Li, Linkai, Xiao Guo, Ming Zhou, et al. "The Investigation of Fracture Networks on Heat Extraction Performance for an Enhanced Geothermal System." Energies 14, no. 6 (2021): 1635. http://dx.doi.org/10.3390/en14061635.

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Hydraulic fracturing is usually employed to create a complex fracture network to enhance heat extraction in the development of an enhanced geothermal system. The heat extraction depends on the heat conduction from the rock matrix to the flowing fractures and the heat convection through a complex fracture network. Therefore, the geometries of the fracture network have important influences on the thermal breakthrough. In this paper, a hydro-thermal coupling mathematical model considering a complex fracture network is established. The embedded discrete fracture model is adopted to explicitly mode

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29

Lou, De Cang, Wen Guo, Zhi Guo Wang, and Yong Hong Wang. "Integrated Thermal Management System Design for Advanced Propulsion System." Applied Mechanics and Materials 232 (November 2012): 723–29. http://dx.doi.org/10.4028/www.scientific.net/amm.232.723.

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Thermal management system (TMS) design is considered to be a key technology for advanced aero engines and supersonic or hypersonic propulsion systems. In this paper, the concepts of coupling flow and thermodynamic networks are proposed for TMS design. In this method, the propulsion system is considered to be a zero-dimensional flow system. Components, subsystems and hence the entire engine system can be modelled using some basic flow and thermodynamics networks. The platform for TMS design, ThermalM, is developed based on this model. As an example, modelling for a Turbine Based Combined Cycle

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Ogunsola, Oluwaseyi T., and Li Song. "Application of a simplified thermal network model for real-time thermal load estimation." Energy and Buildings 96 (June 2015): 309–18. http://dx.doi.org/10.1016/j.enbuild.2015.03.044.

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31

Bornoff, Robin. "Extraction of Boundary Condition Independent Dynamic Compact Thermal Models of LEDs—A Delphi4LED Methodology." Energies 12, no. 9 (2019): 1628. http://dx.doi.org/10.3390/en12091628.

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Multi-domain electro-thermal-optical models of LEDs are required so that their thermal and optical behavior may be predicted during a luminaire design process. Today, no standardized approach exists for the extraction of such models. Therefore, models are not readily provided by LED suppliers to end-users. This results in designers of LED-based luminaires wasting time on LED characterization and ad hoc model extraction themselves. The Delphi4LED project aims to address these deficiencies by identifying standardizable methodologies to extract both electro-optical and thermal compact models of L

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Chen, Ming, Yan Ting Yu, Bo Wang, and Yong Tang. "Test of IGBT Transient Thermal Impedance and Modeling Research on Thermal Model." Advanced Materials Research 148-149 (October 2010): 429–33. http://dx.doi.org/10.4028/www.scientific.net/amr.148-149.429.

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As the operation performances and reliability of semiconductor devices are tightly related to its operating temperature, the research on the heat transfer characteristic and thermal modeling do a significant meaning to extend services lifetime and improve application reliability of the IGBT modules. The physical structure and the conception, RC component network of thermal resistance, test principle and platform of the transient thermal impedance of IGBT module and three modeling methods are briefly introduced. The parameters of Cauer RC thermal network of a certain type IGBT is derived based

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Ahn, Jonghoon. "Thermal Control Processes by Deterministic and Network-Based Models for Energy Use and Control Accuracy in a Building Space." Processes 9, no. 2 (2021): 385. http://dx.doi.org/10.3390/pr9020385.

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Various control approaches for building thermal controls have been studied to improve the energy use which determines a large part of the spatial thermal quality. This research compares the performance of deterministic models and a network-based model to examine the aspects of both energy consumption and thermal comfort. The single-switch deterministic model immediately responds to indoor thermal conditions, but the network-based model sends better-fit signals derived from learned data reflecting seven different climate conditions. As a result, the network-based model improves the thermal comf

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Wang, Yu, Wenjun Duan, Junqing Li, Dongdong Shen, and Peiyong Duan. "Thermal-Adaptation-Behavior-Based Thermal Sensation Evaluation Model with Surveillance Cameras." Sensors 24, no. 4 (2024): 1219. http://dx.doi.org/10.3390/s24041219.

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The construction sector is responsible for almost 30% of the world’s total energy consumption, with a significant portion of this energy being used by heating, ventilation and air-conditioning (HVAC) systems to ensure people’s thermal comfort. In practical applications, the conventional approach to HVAC management in buildings typically involves the manual control of temperature setpoints by facility operators. Nevertheless, the implementation of real-time alterations that are based on the thermal comfort levels of humans inside a building has the potential to dramatically improve the energy e

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Yahia, Zakria Abd El Gawad, I. Youssef Mohamed, and Mahmoud Nasser Tarek. "Medical system based on thermal optical system and neural network." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 4 (2023): 3796–804. https://doi.org/10.11591/ijece.v13i4.pp3796-3804.

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Military personnel in the training or operational phases always need constant medical examination, but the presence of efficient medical care is difficult to implement in real-time for such cases. A wireless system for thermal tracking of soldiers was proposed, as well as tracking their vital signs in real time. Thermal cameras are used with an optical system designed to increase the accuracy of the thermal images captured as the change in the electrocardiogram, heart rate, and temperature measurements are measured using a specially designed circuit. The results from both the thermal system an

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Manikandan, S., and A. J. D. Nanthakumar. "Development of a predictive model for thermal conductivity in graphene nanoplatelets-infused damper oil using ANN/RSM." Thermal Science, no. 00 (2024): 152. http://dx.doi.org/10.2298/tsci231130152m.

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This study aims to develop a predictive model for the thermal conductivity of graphene nanoplatelets/SAE10W oil nanofluids using artificial neural networks and response surface methodology. Generally, the property of thermal conductivity has been measured to enhance the heat transfer efficiency of traditional heat transfer fluids. Experiments were conducted using a thermal constants analyzer at different operating conditions, such as varying the volume concentrations of nanoparticles from 0.050% to 0.150% and increasing the temperature from 20?C to 80?C. Results showed an improvement in the th

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Li, Long, Binyang Chen, Dan Sha, and Chengjun Wang. "Thermal error compensation method of truss robot beam structure based on mechanism and data drive." International Journal of Advanced Robotic Systems 20, no. 2 (2023): 172988062311608. http://dx.doi.org/10.1177/17298806231160878.

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As the main supporting component of the truss robot, the thermal deformation of the beam often has a great influence on the overall thermal error of the truss robot due to its large span. In order to improve the thermal error prediction accuracy of long-span truss robot, a thermal error prediction method based on multiple linear regression and long short-term memory network is proposed based on mechanism and data drive. Firstly, the multiple linear regression model is used to predict the thermal error, and the prediction error data processing. Secondly, the long short-term memory network is es

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Chen, Ming, An Hu, Yong Tang, and Bo Wang. "SABER-Based Simulation for Compact Dynamic Electro-Thermal Modeling Analysis of Power Electronic Devices." Advanced Materials Research 291-294 (July 2011): 1704–8. http://dx.doi.org/10.4028/www.scientific.net/amr.291-294.1704.

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Power electronic modules including insulated gate bipolar transistor (IGBT) are widely used in the field of power converter application. The temperature distribution inside these modules becomes more important for electrical characteristics, reliability and lifetime of integrated power electronic modules. In this paper, a seven-layer compact RC thermal component network model based on the physical structure is presented. A dynamic electro-thermal model, which is composed of electrical model, compact RC thermal component network model and electro-thermal interface is developed for the IGBT. The

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Wu, Hao, Jian Guo Yang, and Xiu Shan Wang. "Synthetically Modeling of Thermal Error and Grinding Force Induced Error on a Precision NC Cylindrical Grinding Machine." Advanced Materials Research 24-25 (September 2007): 243–48. http://dx.doi.org/10.4028/www.scientific.net/amr.24-25.243.

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Thermal errors and force-induced errors are two most significant sources of the NC grinding machine inaccuracy. And error compensation technique is an effective way to improve the manufacturing accuracy of the NC machine tools. Effective compensation relies on an accurate error model that can predict the errors exactly during machining. In this paper, a PSO–BP neural network modeling technique has been developed to build the model of the dynamic and highly nonlinear thermal errors and grinding force induced errors. The PSO–BP neural network modeling technique not only enhances the prediction a

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40

Hylton, Todd. "Thermodynamic Neural Network." Entropy 22, no. 3 (2020): 256. http://dx.doi.org/10.3390/e22030256.

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A thermodynamically motivated neural network model is described that self-organizes to transport charge associated with internal and external potentials while in contact with a thermal reservoir. The model integrates techniques for rapid, large-scale, reversible, conservative equilibration of node states and slow, small-scale, irreversible, dissipative adaptation of the edge states as a means to create multiscale order. All interactions in the network are local and the network structures can be generic and recurrent. Isolated networks show multiscale dynamics, and externally driven networks ev

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Chen, Li Feng, Xiao Ling Wu, Da Tong Qin, and Ze Jun Wen. "Thermal Network Model for Temperature Prediction in Planetary Gear Trains." Applied Mechanics and Materials 86 (August 2011): 415–18. http://dx.doi.org/10.4028/www.scientific.net/amm.86.415.

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Their high-power-density design combined with their limited space make planetary gear trains often high power losses difficult to dissipate to the surround in time. The thermal network model for temperature prediction in planetary gear trains has been proposed. According to the principle of the conservation of energy, the thermal network model have been built and the model have been employed to analyze the transient temperature of the three stage 2K-H planetary gear trains used in Φ6.3m earth pressure balance(EPB) shield machine in series. The computed temperature results of the proposed TNM w

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42

Votinov, M. V., and M. A. Ershov. "Formation of digital counterparts of automatic control objects using neural networks in cold fish drying processes." Vestnik MGTU 25, no. 4 (2022): 291–97. http://dx.doi.org/10.21443/1560-9278-2022-25-4-291-297.

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The paper considers the application of neural networks in the construction of a digital twin of a technological process. The purpose of the presented research is to process the data accumulated by the automatic control system of a small-sized drying plant about the technological processes occurring on it during the last time, to train a neural network on their basis and to form a digital (neural network) model of temperature change in a thermal chamber. Elements of machine learning are used involving a multilayer neural network of direct propagation. The method of error back propagation is use

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43

Ishizuka, Masaru, Tomoyuki Hatakeyama, Yuichi Funawatashi, and katsuhiro Koizumi. "Application of Thermal Network Model to Transient Thermal Analysis of Power Electronic Package Substrate." Active and Passive Electronic Components 2011 (2011): 1–8. http://dx.doi.org/10.1155/2011/823654.

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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

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Trinh, Tan Dat, Pham Cung Le Thien Vu, and Pham The Bao. "Comparing Mask R-CNN backbone architectures for human detection using thermal imaging." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 4 (2024): 3962. http://dx.doi.org/10.11591/ijece.v14i4.pp3962-3970.

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We introduce a method for detecting humans in thermal imaging using an end-to-end deep learning model. Our objective is to optimize the human detection process in thermal imaging by investigating the mask region-based convolutional neural network (Mask R-CNN). The model, an advancement of the faster region-based convolutional neural network (Faster R-CNN), not only captures bounding boxes encompassing human subjects but also delineates segmentation masks around them. Our investigation extends to the evaluation and comparison of various convolutional neural networks for feature learning, like r

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Chang, Yao, Wuhua Li, Haoze Luo, et al. "A 3D Thermal Network Model for Monitoring Imbalanced Thermal Distribution of Press-Pack IGBT Modules in MMC-HVDC Applications." Energies 12, no. 7 (2019): 1319. http://dx.doi.org/10.3390/en12071319.

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In this paper, the impact of a double-sided press-pack insulated-gate-bipolar-transistor (PP IGBT) cooling structure on its thermal impedance distribution is studied and explored. A matrix thermal impedance network model is built by considering the multi-chip thermal coupling effect for the collector side of the PP IGBT. Moreover, a verification has been made by comparing the proposed matrix thermal network model and the conventional lumped RC network model provided by the manufacturer. It is concluded that the collector side has lower thermal resistance and dissipates about 88% of the heat ge

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Duan, Xiaosai, Suihuai Yu, Jianjie Chu, Dengkai Chen, and Yanhao Chen. "Evaluation of Indoor Thermal Environments Using a Novel Predicted Mean Vote Model Based on Artificial Neural Networks." Buildings 12, no. 11 (2022): 1880. http://dx.doi.org/10.3390/buildings12111880.

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The assessment of indoor thermal environments is crucial to achieving thermal comfort and energy efficiency. However, the inaccurate evaluation and strong nonlinear variations of thermal comfort parameters limit engineering designs. Therefore, a coupled heat-transfer model was developed in this study, and large eddy simulations were performed to verify the influence of inertia and buoyancy—which are mutually exclusive forces but coexist in large-space building environments—on inhomogeneous thermal environments. Furthermore, an artificial neural network (ANN) model was designed to overcome the

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Lin, Ze Jin, Jie Hong Yuan, Yuan Li, Xi Jie Yan, Shi Ming Zhou, and Run Jing Chen. "A Temperature Field Model of Complicated Thermal Analysis System Based on Thermal Network Method." Advanced Materials Research 694-697 (May 2013): 695–98. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.695.

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Based on the thermal network method and heat transfer theory, a temperature field simulation model of complicated thermal analysis system was established by Matlab Simulink. Based on the model, a steady-state temperature field of a helicopter tail reducer was calculated in the normal lubrication. The model is more accurate and reliable than the traditional algorithm. Meanwhile, the model can calculate the time-varying process of the temperature field, corresponding to the transient temperature field.

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Gonzalez-Castellanos, Alvaro, Priyanko Guha Thakurta, and Aldo Bischi. "Congestion management via increasing integration of electric and thermal energy infrastructures." E3S Web of Conferences 238 (2021): 05005. http://dx.doi.org/10.1051/e3sconf/202123805005.

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Congestion caused in the electrical network due to renewable generation can be effectively managed by integrating electric and thermal infrastructures, the latter being represented by large scale District Heating (DH) networks, often fed by large combined heat and power (CHP) plants. The CHP plants could further improve the profit margin of district heating multi-utilities by selling electricity in the power market by adjusting the ratio between generated heat and power. The latter is possible only for certain CHP plants, which allow decoupling the two commodities generation, namely the ones p

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Eskandari, Sina, Behrooz Arezoo, and Amir Abdullah. "Thermal Errors Modeling of a CNC Machine’s Axis Using Neural Network and Fuzzy Logic." Applied Mechanics and Materials 110-116 (October 2011): 2976–82. http://dx.doi.org/10.4028/www.scientific.net/amm.110-116.2976.

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Thermal errors of CNC machines have significant effects on precision of a workpiece. One of the approaches to reduce these errors is modeling and on-line compensating them. In this study, thermal errors of an axis of the machine are modeled by means of artificial neural networks along with fuzzy logic. Models are created using experimental data. In neural networks modeling, MLP type which has 2 hidden layers is chosen and it is trained by backpropagation algorithm. Finally, the model is validated with the aid of calculating mean squared error and correlation coefficients between outputs of the

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Tang, Kunhao, Sanhua Zhang, and Youlong Wu. "Optimization and control of fuel cell thermal management system based on neural network." Thermal Science 25, no. 4 Part B (2021): 2933–39. http://dx.doi.org/10.2298/tsci2104933t.

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Aiming at the direct methanol fuel cell system is too complicated, difficult to model, and the thermal management system needs to be optimized. The article attempts to bypass the internal complexity of direct methanol fuel cell, based on experimental data, use neural networks to approximate arbitrarily complex non-linear functions ability to apply neural network identification methods to direct methanol fuel cell, a highly non-linear thermal management system optimization modelling. The paper uses 1000 sets of battery voltage and current density experimental data as training samples and uses a

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