Entropy generation analysis for non-Newtonian nanofluid with zero normal flux of nanoparticles at the stretching surface

• Model is constructed for non-Newtonian nanofluid flow with zero normal flux of nanoparticles at the stretching surface.
• Two important slip mechanism: Brownian motion and Thermophoresis are discussed.
• Entropy generation analysis and heat transfer is discussed for whole phenomena and characteristic entropy generation rate is also calculated at the surface.
• Comparison is made with two different techniques and it is found that entropy generation distribution gives the dominant variation within the non-Newtonian nanofluid with respect to the entropy control parameters.

The primary objective of the present analysis is to investigate the entropy generation via two important slip mechanism Brownian motion and thermophoresis diffusion in non-Newtonian nanofluid flow. These effects are analyzed by momentum equation along with a newly formed equation for nanoparticle distribution. Conventional energy equation is modified for the nanofluid by incorporation nanoparticles effects. The condition for zero normal flux of nanoparticles at the stretching sheet is defined to impulse the particles away from surface. To measure the disorder in the thermodynamic system an entropy generation analysis is discussed for present Jeffery nanofluid model. In order to solve the governing equations, compatible similarity transformations are used to obtain a set of higher order non-linear differential equations. An optimal homotopy analysis method (OHAM) and Keller Box Method are used to solve the given system of higher order nonlinear differential equations. Effect of emerging parameters such as Prandtl number, Schmidt number, Brownian motion and thermophoresis on temperature and concentration are shown through graphs. Variations in the entropy generation for different emerging parameters are discussed in detail with the help of graphical results. Also, the coefficient of skin friction, Nusselt number, Sherwood number and characteristic entropy generation rate are presented through graphs.

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