This article presents a detailed theoretical and computational analysis of alumina and titania-water nanofluid flow from a horizontal stretching sheet. At the boundary of the sheet (wall), velocity slip, thermal slip and Stefan blowing effects are considered. The Pak-Cho viscosity and thermal conductivity model is employed together with the non-homogeneous Buongiorno nanofluid model. The equations for mass, momentum, energy and nanoparticle species conservation are transformed via Lie-group transformations into a dimensionless system. The partial differential boundary value problem is therefore rendered into nonlinear ordinary differential form. With appropriate boundary conditions, the emerging normalized equations are solved with the semi-numerical homotopy analysis method (HAM). To consider entropy generation affects a second law thermodynamic analysis is also carried out. The impact of some physical parameters on the skin friction, Nusselt number, velocity, temperature and entropy generation number (EGM) are represented graphically. This analysis shows that diffusion parameter is a key factor to retards the friction and rate of heat transfer at the surface. Further, temperature of fluid decreases for the higher value of thermal slip parameter. In addition, entropy
In the present framework, flow and thermal transport behavior of non-Newtonian viscoelastic fluid induced by stretching/shrinking of the horizontal sheet under the influence of Lorentz force, volumetric heat source/sink, and radiation (assuming optically thick medium) has been investigated. Multiple solutions (Branches) have been predicted numerically using Lie symmetry transformation and Runge Kutta Dormand Prince (RKDP) algorithm-based Shooting method for the different controlling parameters, stretching/shrinking (𝛾 c < −1 < 𝛾 < ∞), and suction (𝛼 c < 𝛼 < ∞) with substantial impact with UCM parameter, 𝛽 > 0. Some of the results have also been compared with MATLAB built-in solvers to validate our in-house code. The deviations in critical (turning) points (𝛽 c , 𝛾 c ) have been noticed for different values of M and 𝛼. The temporal stability analysis is performed for these parameters (𝛽, 𝛾), and the upper (lower) branch is only physically feasible (infeasible). The combined effect on Nusselt number and skin-friction coefficient is also depicted in the form of contour plots. The outcomes from artificial neural network (ANN) using Levenberg-Marquardt algorithm give a preferred estimate for current numerical simulation. In ANN prediction, the optimal number of neurons in the hidden layer is used, having minimum value of RMSE and RMRE with maximum R 2 for different cases of non Newtonian stretching/shrinking sheet. Finally, the results conclude that the applied ANN model can accurately predict the output results.
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