Advanced Numerical Analysis of Heat Transfer in Medium and Large-Scale Heat Sinks Using Cascaded Lattice Boltzmann Method

Abstract

Medium- and large-scale heat sinks are critical for thermal load management in high-performance systems. However, their high heat flux densities and limited space complicate cooling, leading to risks of overheating, performance degradation, or failure. This study employs the Cascaded Lattice Boltzmann Method (CLBM) to enhance their thermal performance. This numerical approach is known for being stable, accurate when dealing with complex boundaries, and efficient when computing in parallel. The numerical code was validated against a benchmark configuration and an experimental setup to ensure its reliability and accuracy. While previous studies have explored mixed convection in cavities or heat sinks, few have addressed configurations involving side air injection and boundary conditions periodicity in the transition-to-turbulent regime. This gap limits the understanding of realistic cooling strategies for compact systems. Focusing on mixed convection in the transition-to-turbulent regime, where buoyancy and forced convection interact, the study investigates the impact of Rayleigh number values (5×107 to 5×108) and Reynolds number values (103 to 3×103) on heat transfer. Simulations were conducted in a rectangular cavity with periodic boundary conditions on the vertical walls. Two heat sources are located on the bottom wall (Th = 50 °C). Two openings, one on each side of the two hot sources, force a jet of fresh air in from below. An opening at the level of the cavity ceiling’s axis of symmetry evacuates the hot air. Mixed convection drives the flow, exhibiting complex multicellular structures influenced by the control parameters. Calculating the average Nusselt number (Nu) across the surfaces of the heat sink reveals significant dependencies on the Reynolds number. The proposed correlation between Nu and Re, developed specifically for this configuration, fills the current gap and provides valuable insights for optimizing heat transfer efficiency in engineering applications.