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Article | Open Access

MHD (SWCNTS + MWCNTS)/H2O-Based Williamson Hybrid Nanofluids Flow Past Exponential Shrinking Sheet in Porous Medium

Hamzeh Taha Alkasasbeh1( )Muhammad Khairul Anuar Mohamed2
Department of Mathematics, Faculty of Science, Ajloun National University, P.O. Box 43, Ajloun, 26810, Jordan
Centre for Mathematical Sciences, Universiti Malaysia Pahang, Persiaran Lebuhraya Tun Khalil Yaakob, Kuantan, Pahang, 26300, Malaysia
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Abstract

The present study numerically investigates the flow and heat transfer of porous Williamson hybrid nanofluid on an exponentially shrinking sheet with magnetohydrodynamic (MHD) effects. The nonlinear partial differential equations which governed the model are first reduced to a set of ordinary differential equations by using the similarity transformation. Next, the BVP4C solver is applied to solve the equations by considering the pertinent fluid parameters such as the permeability parameter, the magnetic parameter, the Williamson parameter, the nanoparticle volume fractions and the wall mass transfer parameter. The single (SWCNTs) and multi-walled carbon nanotubes (MWCNTs) nanoparticles are taken as the hybrid nanoparticles. It is found that the increase in magnetic parameter in SWCNT + MCWNT hybrid nanofluid results in an increase of 72.2% on skin friction compared to SWCNT nanofluid while maintaining reducing a small number of Nusselt number. This shows the potential of the Williamson hybrid nanofluid for friction application purposes especially in transportation like braking system, flushing fluid and mechanical engineering.

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Frontiers in Heat and Mass Transfer
Pages 265-279

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Cite this article:
Alkasasbeh HT, Mohamed MKA. MHD (SWCNTS + MWCNTS)/H2O-Based Williamson Hybrid Nanofluids Flow Past Exponential Shrinking Sheet in Porous Medium. Frontiers in Heat and Mass Transfer, 2023, 21(1): 265-279. https://doi.org/10.32604/fhmt.2023.041539

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Received: 26 April 2023
Accepted: 09 June 2023
Published: 30 November 2023
© The Author 2024.

This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.