Parametric study and optimization of thermal performance and pressure drop in heat sinks with double-layer porous microchannels

Abstract

In this study, the effective parameters in thermal performance and pressure drop of heat sinks with double-layer porous microchannels were investigated. Initially, a heat sink with porous fins was simulated in ANSYS Fluent 18, and the results were validated against reference data. Subsequently, 340 additional models were simulated with variations in parameters such as microchannel length and width, heat sink wall width and height, inter-channel distance, fluid velocity, and porosity levels (0, 20, 40, 60, and 80 percent). The results indicated that increasing porosity improved thermal performance in all samples, though it also led to higher pressure drops at higher porosity levels. Additionally, parallel flow demonstrated better thermal performance than counter flow across all samples. Reducing the microchannel length and width by 3 times and 4.3 times, respectively, and reducing the microchannel height by up to 4.5 times enhanced thermal performance; however, these changes significantly increased the pressure drop. The effect of flow velocity showed that decreasing the velocity led to a 12-times improvement in thermal performance, yet pressure drop increased by up to 70 times. These findings underscore the importance of optimizing geometric and operational parameters to achieve a balance between high thermal efficiency and acceptable pressure drop in the design of porous heat sinks. In the continuation of the research, the extracted parameters were used as inputs for optimization with a multi-objective genetic algorithm aimed at enhancing thermal performance and reducing pressure drop. Accordingly, the optimization process was pursued using the multi-objective genetic algorithm to find the optimal parameters that achieve the best thermal performance along with the lowest pressure drop, ensuring a desirable balance between improved thermal performance and reduced pressure drop. The convergence results obtained for two parameters in the optimization process demonstrated the success of the optimization method used and confirmed that the optimized parameters can effectively contribute to the enhancement of cooling system performance in industrial applications.