Mathematical and artificial neural network modeling to predict the heat transfer of mixed convective electroosmotic nanofluid flow with Helmholtz-Smoluchowski velocity and multiple slip effects: An application of soft computing-Reference-Cited by-同舟云学术

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Mathematical and artificial neural network modeling to predict the heat transfer of mixed convective electroosmotic nanofluid flow with Helmholtz-Smoluchowski velocity and multiple slip effects: An application of soft computing

Published:2024-09 Issue: Volume:61 Page:104950
ISSN:2214-157X
Container-title:Case Studies in Thermal Engineering
language:en
Short-container-title:Case Studies in Thermal Engineering

Author:

Khan Shan Ali,Farooq Umar,Imran Muhammad,Liu Haihu,Muhammad Taseer,Alghamdi Metib

Funder

King Khalid University

Publisher

Elsevier BV

Reference52 articles.

1. Recent advances in modeling and simulation of nanofluid flows-Part I: fundamentals and theory;Mahian;Phys. Rep.,2019

2. Heat transfer characteristics in nanofluid—a review;Ganvir;Renew. Sustain. Energy Rev.,2017

3. Nanofluid research and applications: a review;Li;Int. Commun. Heat Mass Tran.,2021

4. A review of nanofluid stability properties and characterization in stationary conditions;Ghadimi;Int. J. Heat Mass Tran.,2011

5. Review and comparison of nanofluid thermal conductivity and heat transfer enhancements;Yu;Heat Tran. Eng.,2008

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