Abstract
Three-dimensional steady state numerical simulations are carried out from seven protruding IC chips (Aluminium) of different sizes mounted at various positions on a high-power SMPS board (Bakelite) cooled under forced convection ([Formula: see text][Formula: see text]W/cm2, [Formula: see text][Formula: see text]m/s). The objective is to predict the temperature distribution of these IC chips and to determine their optimal arrangement on the SMPS board; that will have the lowest maximum temperature excess among all the possible configurations. To achieve the same, a numerical analysis is carried out using the commercial software ANSYS-Icepak, and then the hybrid optimization strategy (Genetic Algorithm (GA) driven by Artificial Neural Network (ANN)) is employed to obtain the global optimal configuration of these IC chips. Preliminary analysis is performed using a dimensionless position parameter ([Formula: see text]) which is found to be a strong function of the IC chip size, and their positioning on the substrate board. It is observed that the combined ANN-GA strategy is able to predict the optimal behavior of the IC chips more accurately. The larger size IC chips generating higher power should be placed at the substrate bottom for better cooling.
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