Optimization design of micro-channel heat sink using nanofluid by numerical simulation coupled with genetic algorithm

In this study, microchannel heat sink (MCHS) performance using nanofluid as a coolant is analyzed numerically and nanofluid is modeled using the single phase model and the two phase model. The computational domain is taken as the entire heat sink including the inlet/outlet plenums and micro-channels. Two different types (A type and B type) of MCHS are considered and their thermal resistance for a constant heat flux is compared. The predicted thermal resistance of the B type MCHS shows better than that of the A type MCHS. Furthermore, it is found that single and two-phase models predict almost identical hydrodynamic fields but very different in the thermal fields. The multi-parameter constrained optimization procedure integrates the design of experiments (DOE), and the response surface methodology (RSM) is proposed to design parameters. Genetic algorithm (GA) method is coupled with CFD as an optimization tool. The objective function which is defined as thermal resistance has developed a correlation function with three design parameters. The thermal resistance predicted by regression function for A type and B type MCHS is in good agreement with the numerical results of CFD by the difference within 3.9% and 32%, respectively. (C) 2016 Elsevier Ltd. All rights reserved.