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Autori principali: Santosh L. Pachpute, Kiran C. More
Natura: Artículo Open Access
Pubblicazione: Wiley 2024
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Accesso online:https://onlinelibrary.wiley.com/doi/10.1002/htj.23213
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author Santosh L. Pachpute
Kiran C. More
author_facet Santosh L. Pachpute
Kiran C. More
Santosh L. Pachpute
Kiran C. More
collection Wiley Open Access
contents Design Optimization of a Plate‐Fin Heat Exchanger With Metaheuristic Hybrid Algorithm Santosh L. Pachpute Kiran C. More Heat Transfer ABSTRACTThis paper introduces a novel approach to enhance the heat transfer efficiency of a plate‐fin heat exchanger. The metaheuristic hybrid approach combines particle swarm optimization (PSO) with the genetic algorithm (GA). Seven critical design parameters are used as variables. The research demonstrates the effectiveness of this hybrid method through a case study based on existing literature. The numerical results show the superior performance of the hybrid genetic algorithm particle swarm optimization over conventional GA and PSO techniques. The hybrid method achieves an optimal configuration with increased accuracy in a shorter computational time, offering significant time and cost savings in the design process. 10.1002/htj.23213 http://onlinelibrary.wiley.com/termsAndConditions#vor
doi_str_mv 10.1002/htj.23213
format Artículo Open Access
id wiley_oa_10_1002_htj_23213
institution Wiley Open Access
license_str_mv http://onlinelibrary.wiley.com/termsAndConditions#vor
publishDate 2024
publisher Wiley
record_format wiley_oa
spellingShingle Design Optimization of a Plate‐Fin Heat Exchanger With Metaheuristic Hybrid Algorithm
Santosh L. Pachpute
Kiran C. More
Heat Transfer
Design Optimization of a Plate‐Fin Heat Exchanger With Metaheuristic Hybrid Algorithm Santosh L. Pachpute Kiran C. More Heat Transfer ABSTRACTThis paper introduces a novel approach to enhance the heat transfer efficiency of a plate‐fin heat exchanger. The metaheuristic hybrid approach combines particle swarm optimization (PSO) with the genetic algorithm (GA). Seven critical design parameters are used as variables. The research demonstrates the effectiveness of this hybrid method through a case study based on existing literature. The numerical results show the superior performance of the hybrid genetic algorithm particle swarm optimization over conventional GA and PSO techniques. The hybrid method achieves an optimal configuration with increased accuracy in a shorter computational time, offering significant time and cost savings in the design process. 10.1002/htj.23213 http://onlinelibrary.wiley.com/termsAndConditions#vor
title Design Optimization of a Plate‐Fin Heat Exchanger With Metaheuristic Hybrid Algorithm
topic Heat Transfer
url https://onlinelibrary.wiley.com/doi/10.1002/htj.23213