Heat Transfer Simulation and Temperature Rapid Prediction for Trench Laying Cable

Heat transfer process for trench laying cable is complex. To guarantee safe operation of the cable, it is necessary to predict the temperature and maximum current capacity of trench laying cable rapidly and accurately. Therefore, in this study, an adaptive optimized particle swarm optimization algor...

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Autores principales:	Chen-Zhao Fu, Wen-Rong Si, Ke-Ke Fang, Jian Yang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/091778e95ac94d4d9fe94453acc0e79d
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id	oai:doaj.org-article:091778e95ac94d4d9fe94453acc0e79d
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spelling	oai:doaj.org-article:091778e95ac94d4d9fe94453acc0e79d2021-11-08T02:37:09ZHeat Transfer Simulation and Temperature Rapid Prediction for Trench Laying Cable1563-514710.1155/2021/9271283https://doaj.org/article/091778e95ac94d4d9fe94453acc0e79d2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/9271283https://doaj.org/toc/1563-5147Heat transfer process for trench laying cable is complex. To guarantee safe operation of the cable, it is necessary to predict the temperature and maximum current capacity of trench laying cable rapidly and accurately. Therefore, in this study, an adaptive optimized particle swarm optimization algorithm (LFVPSO) is proposed based on Levy flight algorithm, and it is used to modify the back propagation neural network algorithm (LFVPSO-BPNN). Then, combined with numerical simulations, a network algorithm for temperature prediction of trench laying cable is developed using LFVPSO-BPNN. Finally, the maximum current capacity of four-loop three-phase trench laying cable is calculated using LFVPSO-BPNN together with genetic algorithm (GA&LFVPSO-BPNN). At first, it is found that the LFVPSO-BPNN algorithm proposed in this study is reliable and accurate to predict the cable maximum temperature for different loops (Tmax,i) in the trench. Furthermore, as compared with other similar algorithms, when LFVPSO-BPNN algorithm is used to predict the temperature of trench laying cable, its computation time would be reduced and the prediction accuracy would be improved as well. Second, it is revealed that the effect of ground air temperature (Tsur) on the maximum current capacity of trench laying cable (It,max) is remarkable. As Tsur increases, the It,max for both flat-type and trefoil-type trench laying cable would significantly decrease. In addition, with the same Tsur, the It,max for the flat-type trench laying cable are obviously higher.Chen-Zhao FuWen-Rong SiKe-Ke FangJian YangHindawi LimitedarticleEngineering (General). Civil engineering (General)TA1-2040MathematicsQA1-939ENMathematical Problems in Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
spellingShingle	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939 Chen-Zhao Fu Wen-Rong Si Ke-Ke Fang Jian Yang Heat Transfer Simulation and Temperature Rapid Prediction for Trench Laying Cable
description	Heat transfer process for trench laying cable is complex. To guarantee safe operation of the cable, it is necessary to predict the temperature and maximum current capacity of trench laying cable rapidly and accurately. Therefore, in this study, an adaptive optimized particle swarm optimization algorithm (LFVPSO) is proposed based on Levy flight algorithm, and it is used to modify the back propagation neural network algorithm (LFVPSO-BPNN). Then, combined with numerical simulations, a network algorithm for temperature prediction of trench laying cable is developed using LFVPSO-BPNN. Finally, the maximum current capacity of four-loop three-phase trench laying cable is calculated using LFVPSO-BPNN together with genetic algorithm (GA&LFVPSO-BPNN). At first, it is found that the LFVPSO-BPNN algorithm proposed in this study is reliable and accurate to predict the cable maximum temperature for different loops (Tmax,i) in the trench. Furthermore, as compared with other similar algorithms, when LFVPSO-BPNN algorithm is used to predict the temperature of trench laying cable, its computation time would be reduced and the prediction accuracy would be improved as well. Second, it is revealed that the effect of ground air temperature (Tsur) on the maximum current capacity of trench laying cable (It,max) is remarkable. As Tsur increases, the It,max for both flat-type and trefoil-type trench laying cable would significantly decrease. In addition, with the same Tsur, the It,max for the flat-type trench laying cable are obviously higher.
format	article
author	Chen-Zhao Fu Wen-Rong Si Ke-Ke Fang Jian Yang
author_facet	Chen-Zhao Fu Wen-Rong Si Ke-Ke Fang Jian Yang
author_sort	Chen-Zhao Fu
title	Heat Transfer Simulation and Temperature Rapid Prediction for Trench Laying Cable
title_short	Heat Transfer Simulation and Temperature Rapid Prediction for Trench Laying Cable
title_full	Heat Transfer Simulation and Temperature Rapid Prediction for Trench Laying Cable
title_fullStr	Heat Transfer Simulation and Temperature Rapid Prediction for Trench Laying Cable
title_full_unstemmed	Heat Transfer Simulation and Temperature Rapid Prediction for Trench Laying Cable
title_sort	heat transfer simulation and temperature rapid prediction for trench laying cable
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/091778e95ac94d4d9fe94453acc0e79d
work_keys_str_mv	AT chenzhaofu heattransfersimulationandtemperaturerapidpredictionfortrenchlayingcable AT wenrongsi heattransfersimulationandtemperaturerapidpredictionfortrenchlayingcable AT kekefang heattransfersimulationandtemperaturerapidpredictionfortrenchlayingcable AT jianyang heattransfersimulationandtemperaturerapidpredictionfortrenchlayingcable
_version_	1718442970106036224

Heat Transfer Simulation and Temperature Rapid Prediction for Trench Laying Cable

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