4.7 Article

Cu-Al2O3/Water hybrid nanofluid through a permeable surface in the presence of nonlinear radiation and variable thermal conductivity via LSM

Journal

INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
Volume 126, Issue -, Pages 1347-1356

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijheatmasstransfer.2018.06.005

Keywords

Cu-Al2O3-water hybrid; Stretching surface; Nonlinear thermal radiation; Variable thermal conductivity; Least square method

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This paper scrutinizes the significant effects of nonlinear thermal radiation and time-dependent thermal conductivity due to rotating flow of Cu-Al2O3-water hybrid nanofluid over a three-dimension stretching sheet. The influence of bouncy forces and magnetic field are also considered. The obtained set of partial differential equations (PDEs) converted to a simplified set of ordinary differential equations (ODEs) by introducing the feasible similarity transformation. Least square method (LSM) is adopted to examine the solution of developed model. The obtained solutions are compared with the well-known numerical technique: Runge-Kutta method of order fourth (RK-4). Significant influence of various physical parameters on the velocities and temperature are explained in detailed through graphical representations. Behavior of skin friction coefficient and local Nusselt number due the variation of numerous parameters also discussed in detail. The velocity profiles F' (eta) and G' (eta) for the case of Cu-Al2O3-water are dominant as compare to Cu-water and Al2O3-water while the fluid temperature is dropped for Cu-Al2O3-water case as compare to Cu-water and Al2O3-water. It is noticed that, variation in the Hartmann, porosity and suction/injection parameters cause to increase the friction at the surface. Opposite behavior of skin friction coefficient is observed by increasing the strength of rotational, Grashof number and slip parameter. Obtained results and comparative study witnesses that the least square technique is well-matched with existing results and it can be applied for complex nature models. (C) 2018 Elsevier Ltd. All rights reserved.

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