Engine oil blended Casson hybrid nanofluid flow along a uniformly heated curved surface with Arrhenius activation energy and suction: A computational study

The research studies the numerical analysis of an incompressible Casson hybrid nanofluid, composed of Fe3O4–Cu nanoparticles blended with engine oil, flowing over an exponentially stretched curved surface. It explores the effects of an aligned magnetic field, a uniform heat source, activation energy, and suction while maintaining a low Prandtl number. By employing appropriate similarity transformations, the original partial differential equations are converted into ordinary ones and solved using bvp4c in MATLAB. Graphs and tables depict the influence of dimensionless factors on skin friction coefficient, velocity, thermal, and concentration profiles, as well as Nusselt and Sherwood numbers. The computational findings reveal that magnetic field alignment significantly modifies velocity, decreasing it while uniformly enhancing temperature and concentration profiles. Casson fluid behavior in engine oil amplifies temperature and concentration profiles, thereby enhancing heat and mass transfer rates. Moreover, an increased heat source elevates temperature but reduces overall heat transfer. The chemical reaction parameter diminishes concentration, whereas activation energy enhances it, albeit impacting the mass transfer rate conversely. Additionally, suction increases flow resistance, while the stretching parameter exhibits an inverse effect, both positively influencing heat and mass transfer rates at higher values. Practically, these findings offer insights crucial for optimizing heat exchangers, biomedical devices, and cooling systems, enhancing their efficiency and performance. Additionally, they inform the design of industrial processes involving fluid flow, aiding in the development of more effective and sustainable solutions.