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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
Main Authors: Xu, Zhe, Guo, Yingqing, Yang, Huarui, Mao, Haotian, Yu, Zongling, Zhang, Hang
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Language:English
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cited_by cdi_FETCH-LOGICAL-c273t-74b5ebd9ade7a2b0fa8c0cb41033af01b54d2f0b02bd4f068c4acb2241c13c7c3
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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
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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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source SAGE IMechE Complete Collection; Sage Journals Online
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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