Predicting entropy generation of a hybrid nanofluid in microchannel heat sink with porous fins integrated with high concentration photovoltaic module using artificial neural networks

DOI10.1016/J.ENGANABOUND.2023.02.005zbMath1521.76033OpenAlexW4321014590MaRDI QIDQ6044030

A. R. Teymourtash, Mohammad Passandideh-Fard, Amin Shahsavar, Sajjad Safarzadeh, Marzieh Zamaemifard, Raouf Khosravi

Publication date: 25 May 2023

Published in: Engineering Analysis with Boundary Elements (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.enganabound.2023.02.005

zbMATH Keywords

artificial neural networkmicrochannel heat sinkentropy generationhybrid nanofluidphotovoltaic module

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Non-Newtonian fluids (76A05) Numerical solution to inverse problems in abstract spaces (65J22)

Related Items (1)

Generalized thermal properties of hybrid NANOLIQUID composed of aluminum oxide \((\mathrm{Al_2 O_3})\) and silver (Ag) nanoparticles with water \((\mathrm{H_2O})\) as base liquid

Cites Work

• The performance evaluation of Al\(_2\)O\(_3\)/water nanofluid flow and heat transfer in microchannel heat sink
• Heat transfer in the thermal entrance region for flow through rectangular porous passages
• Convection in Porous Media

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