Boundary Layer Convective Flow in a Divergent Channel With Melting Heat Transfer and Mass Suction/Injection: An Analysis Using ANN and Numerical Methods

Abstract

This study investigates magnetohydrodynamic fluids in converging and diverging channels, with a focus on melting heat transfer effects. The investigation utilizes a combination of numerical techniques, specifically the finite element Galerkin method, and artificial neural network (ANN) modeling to examine fluid flow behavior and thermal patterns in various channel configurations. Numerical explanations are provided for the effect of these factors on temperature, velocity, local skin friction, and Nusselt number distributions. Upon careful analysis and graphical presentation, the acquired data provide a significant understanding of how different physical parameters affect the flow properties. The contrast between the current and past findings reveals a good agreement. The findings have important applications in engineering fields where specific control of fluid flow and heat transfer is essential, including plastic sheet extrusion, electronic device cooling, and metal casting. Additionally, the research employs ANN to enhance the prediction of heat transfer characteristics, demonstrating a strong correlation between predicted and theoretical results. Accurate regulation of fluid flow and heat transmission is crucial in technical areas, such as metal casting, plastic sheet extrusion, and electronic device cooling.