Flow and heat transfer optimization of a fin-tube heat exchanger with vortex generators using Response Surface Methodology and Artificial Neural Network

Using vortex generators (VGs) in fin-tube heat exchangers (FTHEs) is one of the main options to increase their performance. Although numerical models can replace the expensive experimental studies, suggesting an optimum design configuration using numerical models involves trial and error procedures...

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Bibliographic Details
Main Authors:	Changgui Xie, Gongxing Yan, Qiong Ma, Yasser Elmasry, Pradeep Kumar Singh, A.M. Algelany, Makatar Wae-hayee
Format:	Article
Language:	English
Published:	Elsevier 2022-11-01
Series:	Case Studies in Thermal Engineering
Subjects:	Fin-tube heat exchanger Vortex generator Response surface methodology Artificial neural network Heat transfer enhancement
Online Access:	http://www.sciencedirect.com/science/article/pii/S2214157X22006815

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http://www.sciencedirect.com/science/article/pii/S2214157X22006815

Flow and heat transfer optimization of a fin-tube heat exchanger with vortex generators using Response Surface Methodology and Artificial Neural Network

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