Inverse geometric optimization for geometry of nanofluid-cooled microchannel heat sink

Abstract

An inverse geometric optimization for nanofluid-cooled microchannel heat sink (MCHS) considering effects of temperature-dependent thermophyiscal properties for the water-based Al2O3 nanofluid with 1% particle volume fraction was performed under a constant pumping power constraint. A three-dimensional fluid-solid conjugated MCHS model combining the simplified-conjugate-gradient-method was used as the optimization tool. The channel number, N, the channel aspect ratio, α, and the width ratio of channel to pitch, β, affect the cooling performance of MCHS, and were all incorporated in the present, three-parameter optimization study. Increase in viscosity of the nanofluid did not always lead to enhanced MCHS performance under fixed pumping power constraint, contradicting to the results for pure water. The optimal MCHS design is closely related to the assigned pumping power: increase in the pumping power enhances cooling performance; however, in high pumping power regime the performance enhancement is not as effective as in low pumping power regime. At pumping power of 0.05 W and a uniform heat flux of qw = 100 W cm−2, the optimal design for the nanofluid-cooled MCHS presented N = 51, α = 5.69 and β = 0.62, yielding the optimal thermal resistance of RT = 0.1059 K W−1.