Entropy optimization of non-Newtonian hybrid nanofluid flow with non-linear radiation, exponential and thermal dependent heat source: Neuro-intelligent design

Document Type : Article

Authors

Department of Mathematics, VIT, Vellore

Abstract

The prediction of entropy generation with a thermal and exponential space dependent heat source of unsteady flow over a rotating disk is the artifact of the paper. For the specific physical model, non-Newtonian fluids like Oldroyd-B within EMHD fluid flow is encrypted. Also, mechanism of cobalt and tantalum nanoparticles with in the blood is employed. The proper self-similarity variables are used to convert the non-linear PDE system of equations into an ODE form, which is then calculated using the Runge–Kutta 4th with shooting technique and artificial neural network (ANN). Visual representations are used to show how different skewing interact with each other. With a few exceptions, the research findings of the model are quite consistent with those reported in the literature. The skin friction coefficients rise for the increase in the electric field whereas rate of heat transfer declines. Nusselt number and skin frictions decrease for the parameters like radiation, Eckert number, Brinkman number and exponential based heat source. Also, entropy generation rises for magnetic field and Brinkman number whereas opposite tendency is observed for the electric field.

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