Multi-objective optimization of arc-shaped ribs in the channels of a printed circuit heat exchanger

Abstract

Arc-shaped ribs in the cooling channels of a printed circuit heat exchanger have been optimized to enhance heat transfer, and also to reduce the pressure drop based on three-dimensional Reynolds-averaged Navier–Stokes analysis and a multi-objective genetic algorithm with surrogate modeling. The shear stress transport turbulence model was used as the turbulence closure model. Using two geometric design variables (the ratios of the pitch and depth of the ribs to the hydraulic diameter of the channel), two objective functions related to heat transfer and pressure drop in the cold channels were optimized simultaneously. Ten design points were selected in the design space using Latin hypercube sampling, and objective function values were calculated at these design points. Based on these objective function values, surrogate models were constructed to approximate the objective functions. The Pareto-optimal front was obtained by using a multi-objective evolutionary algorithm. Four representative optimal designs were selected on the Pareto-optimal front using k-means clustering. The optimal designs show large increases in both the thermal performance and pressure drop compared to the reference design without ribs.