Multi Objective Optimization of Shell & Tube Heat Exchanger by Genetic, Particle Swarm and Jaya Optimization algorithms; Assessment of Nanofluids as the Coolant

Document Type : Full Lenght Research Article


1 Department of Mechanical Engineering, Tafresh University, Tafresh, Iran

2 Mechanical Energy and Engineering Department, Shahid beheshti university, Tehran, Iran


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 9.66%, 10.63% and 10.9% 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, TiO2 and Al2O3 nanofluids of 0.5% to 5 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.


Main Subjects

Articles in Press, Accepted Manuscript
Available Online from 05 January 2022
  • Receive Date: 13 July 2021
  • Revise Date: 02 January 2022
  • Accept Date: 05 January 2022