Computational study of double diffusive MHD natural convection flow of non-Newtonian fluid between concentric cylinders

This study investigated double diffusion natural convection of Casson fluids in an asymmetrical cavity under a constant magnetic field. The intricacies of flow and heat/mass transfer were explored computationally using the finite element method. Applications exist in geology, oceanography, metallurgy, and astrophysics. The impacts of Rayleigh number, Casson parameter, number of peaks, and Darcy number on entropy generation, velocity, and temperature/concentration gradients were quantified. Key findings showed that by increasing the Rayleigh number, convection chaos and vigor were intensified, thereby boosting gradients. Furthermore, by elevating the Casson parameter, streamlines were narrowed and mixing was reduced owing to more solid-like behavior. Additionally, by varying the number of peaks, flow complexity was modulated, thus allowing for strategic optimization of localized heat/mass transfer rates. Moreover, the Darcy number positively correlated with Nusselt/Sherwood numbers, thus enhancing convection and diffusion. Likewise, elevating Rayleigh number expanded configuration options, consequently increasing system entropy. The computational approach enabled modeling complexity precluded by analytical approaches, while simultaneously providing more insight than experiments. Predictions for entropy, heat transfer, and mixing rates will guide designs for enhanced efficiency and thermal control in applications spanning underground pipelines, boilers, nuclear/thermal plants, and energy storage. Specifically, the strategic modulation of flow parameters to optimize heat transfer and minimize entropy generation will lead to improved energy utilization in high-temperature industrial processes thus advancing sustainability.