Analysis of MHD-Squeezed Darcy-Forchheimer Nanofluid Flow Between h-Distance Horizontal Plates by Computing Approach

Abstract

This study investigates magnetohydrodynamic (MHD) compressed Darcy-Forchheimer nanofluid flow between two parallel plates separated by a distance h and over a nonlinear stretching sheet. The study examines porosity, friction, and a consistently applied magnetic field perpendicular to the lower plate, utilizing the Darcy-Forchheimer porous medium to facilitate horizontal axis flow. We investigate the movement of heat and mass through the examination of Brownian diffusion and thermophoresis. By employing appropriate similarity transformations, the system's highly nonlinear partial differential equations are transformed into ordinary differential equations Hybrid computational methods have been developed by combining the fourth-order Adams-Bashforth numerical method and artificial neural networks optimized with the Levenberg-Marquardt algorithm. These empirical data sets provide the foundation for an artificial neural network model. With both traditional and modern computational techniques available, predictions of parameter combinations for a particular system may be quickly updated. Increased fluid viscosity reduces the rate of movement; however, the combined forces of thermal diffusion and thermophoresis elevate the temperature in the surrounding fluid layer due to thermal gradients and increased surface area.