Computational insights of Casson nanofluid and Newtonian Nanofluid in MHD boundary layer flow over a non-linear stretching sheet with thermal radiation

Abstract

Abstract This study investigates the MHD (magneto-hydrodynamic) unstable boundary layer behaviour of Casson nano fluid flow under the simultaneous influence of thermal radiation over a non-linear stretching sheet. The impact of radiation on both Newtonian and non-Newtonian (Casson) nano fluid flows is analysed. The roles of thermal radiation, Casson nanofluids, and MHD are significant in engineering and industrial applications, including heat exchangers, nuclear reactors, thermal energy storage systems, and advanced drug delivery technologies. The governing partial differential equations are formulated using boundary layer approximations and subsequently transformed into a dimensionless form through suitable similarity variables and parameters. The resulting system of equations is solved numerically using the MATLAB bvp4c solver. The influence of various governing parameters is examined through detailed graphical analysis. The results indicate that Casson fluids exhibit higher velocities and lower friction compared to Newtonian fluids. They show reduced temperature and concentration distributions, while demonstrating enhanced heat and mass transfer rates. The Nusselt number decreases with increasing thermophoresis and Brownian motion parameters, whereas an increase in thermal slip leads to a thinner thermal boundary layer. Stronger magnetic field intensity and higher stretching rates tend to decelerate the flow while elevating temperature and concentration profiles. In contrast, increased suction produces the opposite effect. These results provide useful insights for enhancing thermal management in industrial processes such as polymer extrusion, metal forming, and biomedical systems. A thorough understanding of Casson fluid behaviour is crucial for improving process efficiency, accurately predicting flow characteristics, and ensuring reliable product performance. Moreover, the present model holds significant potential in biomedical applications, particularly for simulating blood flow and evaluating the risk of thrombosis and other cardiovascular disorders.