Stochastic analysis of the MHD flow over a stretching porous surface with variable viscosity

This article investigates numerically and theoretically the thermal transfer rate of an incompressible convective fluid flow over a perforated stretchable sheet in the presence of magnetic dipole with heat-dependent viscosity besides a heating reservoir and sink. This research is useful in optimising the performance of magnetohydrodynamic generators, metal processing units and aerospace crafts. A novel artificial intelligent method of Bayesian algorithm of feed forward neural network, accompanied with Lobatto-IIIA technique is incorporated for optimised results. System of nonlinear PDEs is transformed into ODEs by using suitable dimensionless similarity transformation. Graphical and tabular comparisons are included with error analysis by citing previous studies and their results with the present one. Velocity and temperature profiles are concluded with affected physical parameters of viscosity A, permeability factor k1, thermal radiating parameter as Prandtl quantity Pr, magnetic field tesla as M and sink heat characteristic lambda. It is clearly observed that boundary layer thinning effect amplifies with inclination viscosity and sink heat.