Assorted Graphene-Based Nanofluid Flows Near a Reversed Stagnation Point over an Inclined Permeable Cylinder

Journal Article (2022)
Author(s)

S. N.A. Ghani (Universiti Malaya, Kuala Lumpur)

Hooman Yarmand (TU Delft - Human-Robot Interaction)

Noor Fadiya Mohd Noor (Universiti Malaya, Kuala Lumpur)

Research Group
Human-Robot Interaction
Copyright
© 2022 S. N.A. Ghani, H. Yarmand, N. F.M. Noor
DOI related publication
https://doi.org/10.1007/s40010-022-00782-z
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 S. N.A. Ghani, H. Yarmand, N. F.M. Noor
Research Group
Human-Robot Interaction
Issue number
1
Volume number
93 (2023)
Pages (from-to)
43-55
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Abstract

Heat flux enhancement resulting from utilization of variant graphene-based nanoparticles; graphenes, graphene nanoplatelets, graphene oxides (GOs), carbon nanotubes (CNTs which include single and multiple walled CNTs) in a water-base fluid is focussed in the present study. A steady, laminar, incompressible, mixed convective and reversed stagnation point flow together with the consideration of transverse magnetic field over varying angles of an inclined permeable cylinder is analyzed for the heterogeneous nanofluids. The governing partial differential equations based on Tiwari-Das model are reformulated into nonlinear ordinary differential equations by applying similarity expressions. A shooting procedure is opted to reformulate the equations into boundary value problems which are solved by employing a numerical finite difference code utilizing three-stage Lobatto IIIa formula in MATLAB. The effects of constructive parameters toward the model on non-dimensional velocity and temperature disseminations, reduced skin friction coefficient and reduced Nusselt number are graphically reported and discussed in details. It is observed that GOs-water has the lowest heat flux performance under increasing values of wall permeability parameter, curvature parameter and nanoparticle volume fraction as compared to other nanofluids. On contrary, our results demonstrate that graphenes-water has the highest heat flux performance as compared to SWCNTs-water across many emerging parameters considered in this study.

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