Multi-objective optimization of 3D micro-fins using NSGA-II

Abstract

Because of the great potential for optimization of micro-fin surfaces (< 0.5 mm tall) and the lack of any optimization work encompassing three-dimensional geometries on heat exchanger surfaces, this paper proposes a robust methodology to solve the multi-objective optimization problem with a numerical model and thereby determine the flow physics that characterize the optimal geometries. The micro-fin design variables are considered as micro-fin height, angle, thickness, pitch, length of discontinuity, and number of discontinuities per micro-fin pitch. To reduce computational time, a channel with two-sided periodic domains is presented. A parallelizable numerical model is developed based on Reynolds average Naiver-Stokes equations and a realistic k-ɛ model. The simulation procedure solves convective heat transfer and turbulent flow over micro-fins and solves heat transfer for solid conduction using a constant wall temperature condition to maintain robustness for geometries that do not yield unity fin efficiencies. This study provides a robust methodology to integrate the numerical model into a multi-objective optimization algorithm named non-dominated sorting genetic algorithm II to generate the best trade-off solutions between enhancement of Nusselt number and Fanning friction factor of a micro-fin surface to a smooth surface at two Reynold numbers (Re) of 25,000 and 49,000. This study presents a unique intersection of the drag reduction approach and heat transfer enhancement by finding unique operating geometries. For example, a particular optimal design geometry at Re = 49,000 reduced drag by 8% but was also beneficial to heat transfer increasing by 21% compared to a smooth surface. The best micro-fin surface of this study at Re = 49,000 enhanced the efficiency index by 18% compared to the highest reported efficiency index for micro-fin tubes.