Thermal Radiation-Driven MHD Boundary Layer Dynamics of Hybrid Nanofluids on Porous Exponentially Stretching Sheet

Abstract

This research presents a detailed mathematical analysis of the magnetohydrodynamic (MHD) boundary-layer flow and heat-transfer characteristics of hybrid nanofluids over a porous exponentially stretching sheet in the presence of thermal radiation. Hybrid nanofluids have attracted considerable interest based on their enhanced thermophysical properties compared to conventional mono nanofluids and base fluids. Their superior thermal conductivity provides a novel approach to improving energy transportation in modern thermal systems. In this study, the governing partial differential equations characterizing conservation of mass, momentum, and energy are transformed into a system of nonlinear ordinary differential equations using appropriate similarity transformations. These equations will be solved numerically using the shooting technique in conjunction with the Runge–Kutta–Fehlberg (RKF45) method to provide high accuracy and stability. The effect of important physical parameters, including the magnetic parameter (M), porosity parameter (K), and thermal radiation parameter (Rd), are investigated in detail to ascertain their effect on velocity and temperature distribution in the boundary layer.The findings suggest that by increasing the values of M and K, greater resistive forces (e.g., Lorentz drag and porous-medium resistance) will produce a retardation in the flow of the fluid. Conversely, an arbitrarily large increase in the radiation level will contribute to a significantly increased temperature profile due to increases in radiative energy transfer. The comparison of the hybrid nanofluid and mono-nanofluid models further indicates the heat-transfer capabilities of hybrid nanoparticles are significantly more advantageous, which is expected due to the heat-transfer opportunities afforded by the multiple particles. The skin-friction coefficient and Nusselt numbers are then calculated numerically, with confirmatory values that closely align with previous works to demonstrate validity of the current work.