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Original scientific paper

https://doi.org/10.32985/ijeces.13.7.12

Genetic algorithm for the design and optimization of a shell and tube heat exchanger from a performance point of view

Mohammed Bakr ; Director of the Department of Instrumentation and Control Laboratory, Delta Factory for Fertilizers and Chemical Industries, Computers and Control Systems engineering Department, Faculty of Engineering, University Mansoura, Egypt
Ahmed A. Hegazi ; Mechanical Power Engineering Department, Faculty of Engineering, Mansoura University, El-Mansoura 35516, Egypt
Amira Y. Haikal ; Computers and Control Systems Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt
Mostafa A. Elhosseini ; Computers and Control Systems Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt


Full text: english pdf 2.324 Kb

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Abstract

A new approach to optimize the design of a shell and tube heat exchanger (STHX) is developed via a genetic algorithm (GA) to get the optimal configuration from a performance point of view. The objective is to develop and test a model for optimizing the early design stage of the STHX and solve the design problem quickly. GA is implemented to maximize heat transfer rate while minimizing pressure drop. GA is applied to oil cooler type OKG 33/244, and the results are compared with the original data of the STHX. The simulation outcomes reveal that the STHX's operating performance has been improved, indicating that GA can be successfully employed for the design optimization of STHX from a performance standpoint. A maximum increase in the effectiveness achieves 57% using GA, while the achieved minimum increase is 47%. Furthermore, the average effectiveness of the heat exchanger is 55%, and the number of transfer units (NTU) has improved from 0.475319 to 1.825664 by using GA.

Keywords

Genetic algorithm; Optimization; Overall heat transfer coefficient; Shell and tube heat exchanger

Hrčak ID:

284956

URI

https://hrcak.srce.hr/284956

Publication date:

30.9.2022.

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