Optimization of Micro Heat Sink with Repetitive pattern of Obstacles for Electronic Cooling Applications

Micro Heat Sinks (MHS) are becoming integral part of microelectronics nowadays because of their ability to cool the tiny components which generate high heat flux. In this study, an electronic chip with a high heat flux of 100 W/cm² is cooled with the help of a MHS device which has repetitive patterns of obstacles of various shapes in the flow of cooling medium. Numerical modelling of all MHSs were performed using a Computational Fluid Dynamics (CFD) solver and the pattern, which gives better thermo-hydraulic performance, was selected for optimization. A parametric study was performed with various obstacle sizes, distance between obstacles and flow rate of cooling medium for maximum temperature of chip and pressure drop. Regression analysis was carried out with Response Surface Method (RSM) between these three design variables and two objective functions, viz. thermal resistance (Rth) and pumping power (Pp). A multi-objective optimization of the MHS was performed using genetic algorithm (GA) and pareto-optimal solutions were obtained. An optimal design was fabricated and the cooling experiment was carried out under optimal flow conditions. The repetitive pattern of obstacles increases the conjugate heat transfer area and helps in improving thermal performance.