详细信息

Multi-objective optimization of helically coiled tube heat exchanger based on entropy generation theory  ( SCI-EXPANDED收录 EI收录)  

文献类型:期刊文献

英文题名:Multi-objective optimization of helically coiled tube heat exchanger based on entropy generation theory

作者:Han, Yong[1,2];Wang, Xue-sheng[1];Zhang, Hao-nan[1];Chen, Qin-zhu[1];Zhang, Zhao[1]

机构:[1]East China Univ Sci & Technol, Key Lab Pressure Syst & Safety, Minist Educ, Shanghai 200237, Peoples R China;[2]Zhengzhou Univ Light Ind, Sch Energy & Power Engn, Zhengzhou 450002, Henan, Peoples R China

年份:2020

卷号:147

外文期刊名:INTERNATIONAL JOURNAL OF THERMAL SCIENCES

收录:;EI(收录号:20194407613290);WOS:【SCI-EXPANDED(收录号:WOS:000496937100023)】;

语种:英文

外文关键词:Helically coiled tube heat exchanger; Multi-objective optimization; Entropy generation; Entropy generation number

摘要:In this research, the MOGA optimization was applied to study the design of the helically coiled tube. Firstly, the calculation model was established. Then, the entropy generation number (EGN, N-s) and its variation were investigated. Furthermore, the MOGA optimization under equal Reynolds number was carried out. The results show that: the heat transfer ENG does not always correspond to the heat transfer coefficient; the flow resistance EGN does not always correspond to the flow resistance; there are 3 optimal points for the optimization: A (minimized N-s), B (maximized h & minimized vertical bar Delta p vertical bar) and C (maximized h & minimized vertical bar Delta p vertical bar & minimized N-s); the heat transfer coefficient of C is 6.94% less than B, but flow resistance is 15.7% less than B; the heat transfer coefficient of C is 49.5% larger than A, but flow resistance is 15.8% larger than A; when it comes to the comprehensive performance, C has the best comprehensive performance; B is 10.46% less than C, while A is 22.48% less than C. Consequently, the EGNs cannot fully represent the heat transfer and flow resistance performances. When it combines the comprehensive objective functions as C, the best comprehensive performance can be obtained through optimization.

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