A multi-objective genetic algorithm optimisation of plate-fin heatsinks

Traditional plate-fin heatsinks are used in abundance in data centres and telecommunication systems for electronic integrated circuit and component cooling, without much regard for geometric shape optimisation. Any improvements in the effectiveness of the heatsinks impacts the energy consumed by the information communication and technology (ICT) centres and promote a more sustainable use of raw materials. This paper investigates the optimisation of plate-fin heatsinks in a forced cross-flow using a multi-objective genetic algorithm (MOGA) combined with CFD simulations, by varying the fin angles. The main objective is to improve the heat dissipation rate by modifying geometric parameters (i.e., number, arrangement, and orientation offins). For a generic heat sink test case, the optimised performance is examined in terms of thermal resistance, turbulence intensity, pumping power, coefficient of performance and j-factors. An increase in the effectiveness of heat dissipation is reported ranging from 11.2% to 18.1%.