Prediction of heat transfer coefficient, pressure drop, and overall cost of double-pipe heat exchangers using the artificial neural network-Reference-Cited by-同舟云学术

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Prediction of heat transfer coefficient, pressure drop, and overall cost of double-pipe heat exchangers using the artificial neural network

Published:2022-11 Issue: Volume:39 Page:102391
ISSN:2214-157X
Container-title:Case Studies in Thermal Engineering
language:en
Short-container-title:Case Studies in Thermal Engineering

Author:

Çolak Andaç Batur,Açıkgöz Özgen,Mercan Hatice,Dalkılıç Ahmet Selim,Wongwises Somchai

Funder

Thailand Science Research and Innovation

National Science and Technology Development Agency

Publisher

Elsevier BV

Subject

Fluid Flow and Transfer Processes,Engineering (miscellaneous)

Reference56 articles.

1. Applications of artificial neural networks for thermal analysis of heat exchangers–a review;Mohanraj;Int. J. Therm. Sci.,2015

2. Development of MLP-ANN model to predict the Nusselt number of plain swirl tapes fixed in a counter flow heat exchanger;Devi;Mater. Today Proc.,2021

3. A good contribution of computational fluid dynamics (CFD) and GA-ANN methods to find the best type of helical wire inserted tube in heat exchangers;Sharifi;Int. J. Therm. Sci.,2020

4. Characterization of a triple concentric-tube heat exchanger with corrugated tubes using Artificial Neural Networks (ANN);Moya-Rico;Appl. Therm. Eng.,2019

5. ANN: prediction of an experimental heat transfer analysis of concentric tube heat exchanger with corrugated inner tubes;Verma;Appl. Therm. Eng.,2017

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