Optimization of Transitional Nano-Channel Cooling Heat Sink Using a Genetic Algorithm

Fluid flow in micro/nano-scales channels has received much research interest due to its seemingly endless applications. By entering technology to the area of micro and nano scales, the design and fabrication of miniaturized instruments, such as microelectronics devices, MEMS, NEMS and ..., become very desirable. In such small sizes, the performance of the devices can be affected by some undesired small scale world phenomena. One of them is the generated heat in miniaturized devices that has suicidal effect on the performance of the devices and must be removed. The traditional cooling methods, such as free convection of air, are not enough efficient for cooling of these devices, therefore, other effective methods must be considered. Using nano- and micro-channels as heat sinks is one of the most effective methods for cooling the miniaturized devices. Increasing cooling performance and decreasing pressure drop along the channels are two important factors in designing nanochannels as a heat sink. Optimized design of cooling systems has significant effect on improving cooling performance and energy management of the devices. In this study, using a Genetic Algorithm technique, it is desired to find the optimized design for the cooling performance of transitional nano-channel heat sink.