Analysis of the effect of roughness and concentration of Fe3O4/water nanofluid on the boiling heat transfer using the artificial neural network: An experimental and numerical study

Since experimental studies in the field of nanofluid pool boiling requires costly and time-consuming tests, numerical methods such as artificial neural networks with higher predictability and nonlinear features are suitable for prediction and modeling of problem parameters. In this paper, 180 pool b...

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Veröffentlicht in:	International journal of thermal sciences Jg. 163; S. 106863
Hauptverfasser:	Peng, Yeping, Ghahnaviyeh, Milad Boroumand, Ahmad, Mohammad Nazir, Abdollahi, Ali, Bagherzadeh, Seyed Amin, Azimy, Hamidreza, Mosavi, Amirhosein, Karimipour, Aliakbar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Masson SAS 01.05.2021
Schlagworte:	Artificial neural network BHTC Fe3O4/Water nanofluid Multi-objective genetic algorithm Pool boiling Surface roughness Multi-objective genetic algorithm BHTC Surface roughness Artificial neural network Fe3O4/Water nanofluid Pool boiling
ISSN:	1290-0729, 1778-4166
Online-Zugang:	Volltext
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