Evaluation of Heat Transfer and Fluid Dynamics across a Backward Facing Step for Mobile Cooling Applications Utilizing CNT Nanofluid in Laminar Conditions

Abstract

In a variety of engineering applications, the efficacy of heat dissipation in mobile cooling systems is greatly influenced by the Backward Facing Step. Its significance in optimizing cooling solutions for mobile devices is highlighted by the fact that its design and fluid dynamics are crucial in minimizing skin friction and improving passive heat transfer. In this paper, we present a verification of an advanced numerical model for heat transfer and fluid flow through a Backward Facing Step, used in mobile cooling. The objective of this study is to explore fluid separation, a method enhancing passive heat transfer and reducing skin friction. ANSYS/FLUENT software has been used to solve the backward facing step in a horizontal duct filled with pure water. Carbon nanotube (CNT) dispresed into the base fluid at different volume fractions of 0.2%, 0.65%, and 1%. This study focused on laminar flow conditions ranging from Reynolds numbers 200 to 900. In order to reduce the computation time and ensuring the accuracy and reliability of numerical simulations, a grid independence study has been conducted. The findings revealed a substantial rise in the average Nusselt number and heat transfer coefficient with increased Reynolds number and volume fraction of nanoparticles. Specifically, the nanofluid (CNT/water) exhibited the highest average Nusselt number and heat transfer coefficient with volume fractions 1%. Furthermore, the research showed a decrease in the skin friction factor as both Reynolds number increased and nanoparticles’ volume fraction decreased. The increments of nanoparticles' concentrations lead to increase viscosity, promotes agglomeration, alters flow behaviour by inducing turbulence, and enhances heat transfer. These factors collectively contribute to higher skin friction due to increased resistance to fluid flow and disrupted streamline patterns