Multi-Objective Optimization of the Perforated Micro Pin-Fin Heat Sink Using Non-Dominated Sorting Genetic Algorithm-II Coupled With Computational Fluid Dynamics Simulation

Abstract

Abstract This paper numerically investigates the optimization of the geometric parameters and the coolant's inflow states of the perforated micropin-fins (MPFs) heat sink using an elitist nondominated sorting genetic algorithm-II (NSGA-II) coupled with a finite volume-based computational fluid dynamics (CFD) solver. Square-shaped MPFs with two circular perforations were considered for the investigations on the fluid flow and conjugate heat transfer using numerical simulations. Five design variables (two perforation diameters, their respective locations, and the inflow velocity) with the essential constrained equations were optimized to search for the optimal solutions. Two objective functions, viz., Nusselt number (Nu) and friction factor (f), were selected to evaluate the hydrothermal performances of the perforated MPFs heat sink. The optimization was performed for 52 generations with a population size of 30. We obtained the Pareto optimal solutions, which gave the design boundary of the important parameters. Some of the cases of the Pareto solutions were also investigated in detail to understand the underlying thermal physics and structural rigidity under thermal and hydraulic stresses. It is observed that the MPF's stiffness was not compromised upon introducing two perforations. This study identified different thermohydraulic features responsible for optimal performance at different inflow velocity regimes. The present paper demonstrates that this optimization technique has led to a better understanding of the underlying thermal physics of complex electronic cooling equipment while systematically exploring the design space.