Design Optimization of Manifold Microchannel Heat Sink using Evolutionary Algorithms

\nIn today’s world, miniaturized products are proved to be the dis-ruptive technologies contributing to the sustainability through green energy. Microchannel heat sink (MCHS) is an advanced cooling device to accom-plish the cooling requirements for such miniaturized products through sus-tainable approach. In this work, two popular Nature Inspired Swarm Intelli-gence algorithms viz. Teaching Learning Based Optimization (TLBO) and Particle swarm optimization (PSO) are applied for optimizing the perfor-mance of MCHS through maximizing the Thermal resistance & Minimizing the Pumping Power of MCHS. Results are compared with the numerical analysis and GA. For the objective function thermal resistance, results of TLBO and PSO algorithms are improved by 8 % as compared with numeri-cal solutions. For pumping power problem, significant improvement in the results viz. 90.86% is observed with TLBO and PSO algorithm respectively. This optimized design can be directly adopted and it ensures the optimized cooling through equal sharing of thermal load by every channel and thereby minimizing the pump energy consumption. This work demonstrates the ap-plicability of contemporary Nature Inspired Artificial Intelligence (AI) based algorithms in the domain of Heat Sinks and a step towards a green energy.\n