Heat transfer analysis of mixed convective hybrid nanofluid flow with variable permeability

The main focus of this study is to enhance the thermal performance of oil-cooled engines with the help of hybrid nanofluid in the automobile industry. The problem arises from the fact that conventional fluids are inadequate to enable efficient heat absorption and generation issues in industrial sectors. The present work examines how thermal dispersion affects the fluid in a non-Darcy porous medium over a vertical cylinder. In addition, mixed convection, variable permeability, and hybrid nanofluids are utilized to model the present boundary layer problem. A combination of hybrid nanofluids is chosen as carbon nanotubes, due to its temperature resistant property. Engine Oil is used as a base fluid which plays a vital role in lubrication and cooling process. The promising thermophysical properties of nanoparticles and Engine Oil are considered at 27∘C. Moreover, the effects of Engine Oil at 10∘C, 20∘C, 30∘C, and 40∘C are analyzed to detect the heat transfer augmentation. The numerical findings of the converted system are solved by the bvp4c solver through MATLAB. The graphical results explore the strengthened temperature distribution, as the nanoparticle’s volume fraction enhances. Also, the numerical outcomes are validated with existing literature. Furthermore, the numerical results are explored for different fluid temperatures of Engine Oil. The thermal dispersion model-based simulations demonstrate an increase in thermal conductivity at maximum velocity. Based on these simulations, the results showed that the fluid’s surface area and heat transmission capacity is increased by the suspended solid nanoparticle volume fraction. The average Nusselt number improves as the solid volume fraction improves. Furthermore, considerable improvement in thermal conductivity is observed for Ag−SWCNT/EO. The Ag−SWCNT/EO achieve more heat transfer than CuO−MWCNT/EO. We also examined the effects of the variable permeability variation on the physical parameters of the problem.