Abstract
In this research, we explore the potential of magnetohydrodynamic (MHD) bioconvective nanofluids with varying viscosity through non-similarity analysis, aiming to enhance the thermal performance of biological and industrial systems. Recent years have witnessed significant advancements in energy applications, motivating our investigation. To enhance heat transfer, we employ propylene glycol as the base liquid, incorporating silicon dioxide and molybdenum disulfide nanomaterials. This unique configuration enables efficient heat dissipation and accommodates inner heat sources or sinks. Our model relies on partial differentials, and we derive a non-similar dimensionless representation of the governing system using appropriate transformations. We utilize ordinary differential equations (ODEs), approximating local non-similarity (LNS), to estimate transformed non-similar partial differential equations (PDEs). Numerical simulations are performed using the bvp4c algorithm. Throughout our analysis, we present various physical parameters, demonstrating their importance in fluid flow and thermal transport through graphical and tabular representations. Our findings show that alterations in the magnetic parameter lead to changes in fluid velocity and temperature profiles. Similarly, adjustments in the viscosity parameter affect fluid velocity, and variations in the temperature-dependent viscosity parameter influence velocity profiles, with temperature profiles responding to changes in the Brinkman number and heat source parameter. Additionally, we observe concentration profile adjustments with shifts in the Schmidt number and enhanced migration of particles or components within the nanofluid with rising Soret numbers, impacting the concentration profile. Furthermore, an increased Peclet number positively influences microorganism profiles, while the Lewis number exhibits contrasting behavior. To further validate our approach, we present comparative analyses of skin friction coefficients and Nusselt numbers in tabular form. Our primary objective in this study is to formulate non-similar transformations tailored to the specific problem under consideration. These transformations aim to produce accurate and efficient results, providing valuable insights for future research endeavors in the field of nanofluid flows.
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