Multi Objective Optimization of Shell & Tube Heat Exchanger by Genetic, Particle Swarm and Jaya Optimization algorithms; Assessment of Nanofluids as the Coolant
Publish place: Journal of Heat and Mass Transfer Research، Vol: 9، Issue: 1
Publish Year: 1401
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JHMTR-9-1_001
تاریخ نمایه سازی: 24 شهریور 1403
Abstract:
In this study, the design of a nanofluid driven shell and tube heat exchanger is optimized, for the first time, by use of three multi objective algorithms. Two different operating conditions are investigated to compare the performance of the algorithms based on an economic model (cost function). Based on the obtained results, the Genetic, Particle Swarm and Jaya optimization algorithms can all improve the design. The amount of design improvement by each method is ۹.۶۶%, ۱۰.۶۳% and ۱۰.۹% respectively. Also from the view point of optimization time, Jaya optimization algorithm has relatively less CPU time than the other two algorithms, which in fact, reduces computational costs in complicated computations. Finally, due to the good performance of Jaya optimization algorithm in comparison with other considered algorithms, the performance of the heat exchangers is evaluated for using Ag, TiO۲ and Al۲O۳ nanofluids of ۰.۵% to ۵ vol.% by this algorithm. A performance evaluation factor (PE) is introduced as the criterion for simultaneous investigation of thermal and hydraulic performance of nanofluids. The results show that silver nanofluid, among other ones has better performance.
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Authors
Zahra Baniamerian
Department of Mechanical Engineering, Tafresh University, Tafresh, Iran
Ali Karimi
Mechanical Energy and Engineering Department, Shahid beheshti university, Tehran, Iran
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