Brownian motion effects and thermophoresis on heat transmission mechanism of hybrid nano liquid flow over a stretched wedge surface - Sharanayya Swami; Suresh Biradar; Jagadish V Tawade; Vediyappan Govindan; Haewon Byeon; Busayamas Pimpunchat (Partial Differential Equations in Applied Mathematics)
The current study observes the impact of thermophoresis, Brownian motion, and magnetic fields on the flow and heat transfer properties of a hybrid nanofluid containing Al2O3, CuO, and ethylene glycol over a wedge-shaped surface undergoing horizontal stretching. The study addresses the critical need to enhance energy transfer and thermal management systems, which have significant technical and industrial applications. To model the problem, flow equations were transformed into ordinary differential equations using similarity transformations and solved numerically via the Runge-Kutta-Fehlberg method. The results reveal that the wedge angle and magnetic field strength are crucial factors influencing the flow and thermal behavior. Specifically, increasing the wedge angle enhances the Nusselt number but reduces the thermal and diffusion profiles. The suction and injection of the fluid significantly impact the local heat transfer rates and boundary layer thickness. Additionally, the Buongiorno slip parameter reduces the rate of energy transfer while amplifying thermal distributions. The thermophoresis parameter was found to influence both concentration and thermal boundary layers. A comparative analysis between Newtonian and non-Newtonian fluids showed that hybrid nanofluids improve mass and energy transfer rates in both cases, with enhanced effects observed in non-Newtonian fluids. The study's novelty lies in its comprehensive exploration of magneto-flow dynamics and hybrid nanofluid behavior in the context of wedge geometries and external magnetic fields. The findings extend previous research by offering quantitative insights into how key parameters like wedge angles, thermophoresis, and Brownian motion affect heat and mass transfer processes, providing a robust framework for optimizing hybrid nanofluid applications in engineering and industrial systems. The results align well with existing literature, validating the study's contributions to the field.