Supervised machine learning computing paradigm to measure melting and dissipative effects in entropy induced Darcy–Forchheimer flow with ternary-hybrid nanofluids-Reference-Cited by-同舟云学术

Supervised machine learning computing paradigm to measure melting and dissipative effects in entropy induced Darcy–Forchheimer flow with ternary-hybrid nanofluids

Published:2024-07-14 Issue: Volume: Page:1-22
ISSN:1040-7790
Container-title:Numerical Heat Transfer, Part B: Fundamentals
language:en
Short-container-title:Numerical Heat Transfer, Part B: Fundamentals

Author:

Qureshi Hamid¹,Shah Zahoor²,Raja Muhammad Asif Zahoor³^ORCID,Shoaib Muhammad⁴,Khan Waqar Azeem¹

Affiliation:

1. Department of Mathematics, Mohi-Ud-Din Islamic University, Nerian Sharif AJK, Pakistan

2. Department of Mathematics, COMSATS University Islamabad, Islamabad Campus, Pakistan

3. Future Technology Research Center, National Yunlin University of Science and Technology, Douliou, ROC

4. AI Center, Yuan Ze University, Taoyuan, ROC

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10407790.2024.2377794

Reference53 articles.

1. Interlaboratory comparison of size measurements on nanoparticles using nanoparticle tracking analysis (NTA)

2. An Experimental Investigation into the Thermal Properties of Nano Fluid

3. Developments and future insights of using nanofluids for heat transfer enhancements in thermal systems: a review of recent literature

4. Hybrid nanofluid flow and heat transfer over a nonlinear permeable stretching/shrinking surface

5. Thermal analysis for hybrid nanofluid past a cylinder exposed to magnetic field

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Stochastic computing with Levenberg–Marquardt neural networks for the study of radiative transportation phenomena in three-dimensional Carreau nanofluid model subjected to activation energy and porous medium;Chemical Engineering Journal Advances;2024-11