Numerical simulation of heat transfer and flow of AlO-water nanofluid in microchannel heat sink with cantor fractal structure based on genetic algorithm.

The heat generated during operation of microelectronic devices often adversely affects product performance. A remedy for this problem can be through the incorporation of nanofluidic microchannel heat sinks. Advanced working fluids and channel structures can be used to improve the heat transfer performance of the microchannel heat sink. First, thermal resistance is treated as a single objective function, the geometry of the microchannel was optimized using a genetic algorithm. The flow and heat transfer characteristics of the optimized microchannel are analyzed. The effect of different nanofluid volume fractions and geometric parameters on the inlet and outlet pressure drop, flow resistance coefficient, substrate temperature, Nusselt number (Nu), and system thermal resistance in the fractal microchannel are investigated. The thermal resistance of Al2O3 nanofluid with a volume fraction of 5% is 12.5-14.7% lower than that of deionized water, and the microchannel substrate temperature is 6.26 °C lower than that of deionized water.