A Genetic Algorithm Based Multi-Objective Thermal Design Optimization of Liquid Cooled Offset Strip Fin Heat Sinks

A genetic algorithm based multi-objective thermal design optimization of liquid cooled offset strip fin heat sinks is presented. Using water and HFE-7000 as coolants, Matlab’s genetic algorithm and direct search toolbox functions were utilized to determine the optimal thermal design of the offset strip fin heat sink based on the total thermal resistance and power consumption under constant pressure drop. For a relatively small fin length, the total thermal resistance decreases with increasing fin length and aspect ratio α. For larger fin lengths, the total thermal resistance increases with increasing fin length whereas the power consumption continuously increases with increasing fin length and aspect ratio α for a given pressure drop. A plot of the Pareto front indicates a trade-off between the total thermal resistance and pumping power consumption.