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Performance calculation and configuration optimization of annular radiator by heat transfer unit simulation and a multi-objective genetic algorithm
A performance calculation method based on heat transfer unit (HTU) simulation is proposed to calculate heat transfer capacity and air-side pressure drop of Annular radiator (AR), which can avoid the problem of a huge amount of grids, and at the same time, ensure the calculation accuracy. Calculation...
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Published in: | Proceedings of the Institution of Mechanical Engineers. Part E, Journal of process mechanical engineering Journal of process mechanical engineering, 2021-10, Vol.235 (5), p.1292-1303 |
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container_title | Proceedings of the Institution of Mechanical Engineers. Part E, Journal of process mechanical engineering |
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creator | Xu, Zhe Guo, Yingqing Yang, Huarui Mao, Haotian Yu, Zongling Zhang, Hang |
description | A performance calculation method based on heat transfer unit (HTU) simulation is proposed to calculate heat transfer capacity and air-side pressure drop of Annular radiator (AR), which can avoid the problem of a huge amount of grids, and at the same time, ensure the calculation accuracy. Calculation results are compared with experimental data, and the average errors of heat transfer capacity and air-side pressure drop are 11.5%, and 5.9%, respectively, which effectively validates the effectiveness and the reliability of this method. Besides, based on HTU simulation knowledge database, a configuration optimization method of AR using Non-dominated Sorted Genetic Algorithm-II (NSGA-II) is introduced. Number of fins in circumferential direction, number of fins in axial direction, and fin height are chosen as design parameters, and two conflicting optimization objectives include heat transfer capacity maximization and air-side pressure drop minimization. Three optimal structures of AR are obtained, and the optimal results indicate that the heat transfer capacity of the optimal configurations increases by 34.31% on average compared with the original one, while the air-side pressure drop decreases by 24.00% on average, which indicates that this method is feasible and valid and can provide significant guidance for structural design of AR. |
doi_str_mv | 10.1177/09544089211001792 |
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Calculation results are compared with experimental data, and the average errors of heat transfer capacity and air-side pressure drop are 11.5%, and 5.9%, respectively, which effectively validates the effectiveness and the reliability of this method. Besides, based on HTU simulation knowledge database, a configuration optimization method of AR using Non-dominated Sorted Genetic Algorithm-II (NSGA-II) is introduced. Number of fins in circumferential direction, number of fins in axial direction, and fin height are chosen as design parameters, and two conflicting optimization objectives include heat transfer capacity maximization and air-side pressure drop minimization. Three optimal structures of AR are obtained, and the optimal results indicate that the heat transfer capacity of the optimal configurations increases by 34.31% on average compared with the original one, while the air-side pressure drop decreases by 24.00% on average, which indicates that this method is feasible and valid and can provide significant guidance for structural design of AR.</description><identifier>ISSN: 0954-4089</identifier><identifier>EISSN: 2041-3009</identifier><identifier>DOI: 10.1177/09544089211001792</identifier><language>eng</language><publisher>London: SAGE PUBLICATIONS, INC</publisher><subject>Configuration management ; Design optimization ; Design parameters ; Fins ; Genetic algorithms ; Heat transfer ; Mathematical analysis ; Multiple objective analysis ; Optimization ; Pressure drop ; Radiators ; Simulation ; Structural design</subject><ispartof>Proceedings of the Institution of Mechanical Engineers. 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Part E, Journal of process mechanical engineering</title><description>A performance calculation method based on heat transfer unit (HTU) simulation is proposed to calculate heat transfer capacity and air-side pressure drop of Annular radiator (AR), which can avoid the problem of a huge amount of grids, and at the same time, ensure the calculation accuracy. Calculation results are compared with experimental data, and the average errors of heat transfer capacity and air-side pressure drop are 11.5%, and 5.9%, respectively, which effectively validates the effectiveness and the reliability of this method. Besides, based on HTU simulation knowledge database, a configuration optimization method of AR using Non-dominated Sorted Genetic Algorithm-II (NSGA-II) is introduced. Number of fins in circumferential direction, number of fins in axial direction, and fin height are chosen as design parameters, and two conflicting optimization objectives include heat transfer capacity maximization and air-side pressure drop minimization. Three optimal structures of AR are obtained, and the optimal results indicate that the heat transfer capacity of the optimal configurations increases by 34.31% on average compared with the original one, while the air-side pressure drop decreases by 24.00% on average, which indicates that this method is feasible and valid and can provide significant guidance for structural design of AR.</description><subject>Configuration management</subject><subject>Design optimization</subject><subject>Design parameters</subject><subject>Fins</subject><subject>Genetic algorithms</subject><subject>Heat transfer</subject><subject>Mathematical analysis</subject><subject>Multiple objective analysis</subject><subject>Optimization</subject><subject>Pressure drop</subject><subject>Radiators</subject><subject>Simulation</subject><subject>Structural design</subject><issn>0954-4089</issn><issn>2041-3009</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNplkE9LAzEQxYMoWKsfwFvA8-okm226Ryn-g4Ie9LxMskmbspvUJCvUr-EXdkt7EJzL8GZ-vAePkGsGt4xJeQd1JQTMa84YAJM1PyETDoIVJUB9Sib7f7EHzslFShsYR4CckJ83E22IPXptqMZODx1mFzxF31IdvHWrIR4uYZtd776Pwo6EH-FII7YOc4hU7ejaYKY5ok_WRDp4l2ly_V9PpKPMrghqY3R2X4aujDfZaYrdKkSX1_0lObPYJXN13FPy8fjwvngulq9PL4v7ZaG5LHMhhaqMamtsjUSuwOJcg1aCQVmiBaYq0XILCrhqhYXZXAvUinPBNCu11OWU3Bx8tzF8DiblZhOG6MfIhldyxudcjEFTwg6UjiGlaGyzja7HuGsYNPvum3_dl79WPHsy</recordid><startdate>202110</startdate><enddate>202110</enddate><creator>Xu, Zhe</creator><creator>Guo, Yingqing</creator><creator>Yang, Huarui</creator><creator>Mao, Haotian</creator><creator>Yu, Zongling</creator><creator>Zhang, Hang</creator><general>SAGE PUBLICATIONS, INC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><orcidid>https://orcid.org/0000-0002-7598-9939</orcidid></search><sort><creationdate>202110</creationdate><title>Performance calculation and configuration optimization of annular radiator by heat transfer unit simulation and a multi-objective genetic algorithm</title><author>Xu, Zhe ; Guo, Yingqing ; Yang, Huarui ; Mao, Haotian ; Yu, Zongling ; Zhang, Hang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c273t-74b5ebd9ade7a2b0fa8c0cb41033af01b54d2f0b02bd4f068c4acb2241c13c7c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Configuration management</topic><topic>Design optimization</topic><topic>Design parameters</topic><topic>Fins</topic><topic>Genetic algorithms</topic><topic>Heat transfer</topic><topic>Mathematical analysis</topic><topic>Multiple objective analysis</topic><topic>Optimization</topic><topic>Pressure drop</topic><topic>Radiators</topic><topic>Simulation</topic><topic>Structural design</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xu, Zhe</creatorcontrib><creatorcontrib>Guo, Yingqing</creatorcontrib><creatorcontrib>Yang, Huarui</creatorcontrib><creatorcontrib>Mao, Haotian</creatorcontrib><creatorcontrib>Yu, Zongling</creatorcontrib><creatorcontrib>Zhang, Hang</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>Proceedings of the Institution of Mechanical Engineers. Part E, Journal of process mechanical engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xu, Zhe</au><au>Guo, Yingqing</au><au>Yang, Huarui</au><au>Mao, Haotian</au><au>Yu, Zongling</au><au>Zhang, Hang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Performance calculation and configuration optimization of annular radiator by heat transfer unit simulation and a multi-objective genetic algorithm</atitle><jtitle>Proceedings of the Institution of Mechanical Engineers. Part E, Journal of process mechanical engineering</jtitle><date>2021-10</date><risdate>2021</risdate><volume>235</volume><issue>5</issue><spage>1292</spage><epage>1303</epage><pages>1292-1303</pages><issn>0954-4089</issn><eissn>2041-3009</eissn><abstract>A performance calculation method based on heat transfer unit (HTU) simulation is proposed to calculate heat transfer capacity and air-side pressure drop of Annular radiator (AR), which can avoid the problem of a huge amount of grids, and at the same time, ensure the calculation accuracy. Calculation results are compared with experimental data, and the average errors of heat transfer capacity and air-side pressure drop are 11.5%, and 5.9%, respectively, which effectively validates the effectiveness and the reliability of this method. Besides, based on HTU simulation knowledge database, a configuration optimization method of AR using Non-dominated Sorted Genetic Algorithm-II (NSGA-II) is introduced. Number of fins in circumferential direction, number of fins in axial direction, and fin height are chosen as design parameters, and two conflicting optimization objectives include heat transfer capacity maximization and air-side pressure drop minimization. Three optimal structures of AR are obtained, and the optimal results indicate that the heat transfer capacity of the optimal configurations increases by 34.31% on average compared with the original one, while the air-side pressure drop decreases by 24.00% on average, which indicates that this method is feasible and valid and can provide significant guidance for structural design of AR.</abstract><cop>London</cop><pub>SAGE PUBLICATIONS, INC</pub><doi>10.1177/09544089211001792</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-7598-9939</orcidid></addata></record> |
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subjects | Configuration management Design optimization Design parameters Fins Genetic algorithms Heat transfer Mathematical analysis Multiple objective analysis Optimization Pressure drop Radiators Simulation Structural design |
title | Performance calculation and configuration optimization of annular radiator by heat transfer unit simulation and a multi-objective genetic algorithm |
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