Abstracts

Artificial Neural Network and BVP4c Based Analysis of Electromagnetic Micropolar Fluid Flow and Heat Transfer over a Melting Stretching Surface

Dharmendra Tripati, National Institute of Technology Uttarakhand

This invited talk presents a numerical investigation of electromagnetic effects on micropolar fluid flow and heat transfer over a stretching sheet with melting surface and viscous dissipation using Artificial Neural Networks (ANN) and the BVP4c solver. The coupled nonlinear boundary layer equations are solved through both approaches to evaluate their accuracy and computational efficiency in handling complex boundary value problems. Results demonstrate that the micropolar material parameter and magnetic field reduce fluid velocity due to enhanced rotational resistance and Lorentz force effects, respectively. In contrast, electric field and Hall current significantly influence the velocity and angular velocity distributions. The melting parameter strongly affects momentum and thermal boundary layers, leading to reduced velocity and microrotation near the surface. A close agreement between ANN and BVP4c solutions validates the reliability of machine learning assisted numerical methods for nonlinear transport phenomena. The study highlights the importance of coupled electromagnetic, thermal, and micropolar effects in advanced engineering systems such as polymer extrusion, MHD generators, cooling technologies, and smart material processing.

Keywords: Artificial Neural Networks (ANN); BVP4c Solver; Micropolar Fluid; Electromagnetic Flow; Heat Transfer; Melting Surface; Stretching Sheet.