Multi-Objective Optimization of a Microchannel Membrane-Based Absorber with Inclined Grooves Based on CFD and Machine Learning

Abstract

A novel microchannel membrane-based absorber with inclined grooves is proposed and studied by a three-dimensional CFD model. Parametric analysis is carried out to analyze the effects of structural parameters on the absorption rate and pressure drop. Results indicate that the groove introduces a swirling effect in the solution channel, interrupting the boundary layer at the solution-membrane interface and increasing the solution residence time inside the microchannel. The absorption rate in the grooved channel is up to 1.55 times higher, while the pressure drop is 0.77 -0.96 times lower. To optimize the novel absorber geometries and maximize the integrated performance, the Pareto front is obtained by performing a multi-objective optimization, in which a machine learning method based on ANN and NSGA-II is developed. The optimal design parameters from the Pareto front are identified by two well-known decision-making methods, LINMAP and TOPSIS. Compared to the basic smooth channel, these methods generate 1.41 and 1.47 times improvement in volumetric cooling capacities, at a much lower solution pressure drop. Moreover, a high absorption rate equivalent to that of a 200 mm-thick smooth channel is achieved by LINMAP and TOPSIS, with pressure drops lower by 6.29 and 5.63 times, respectively.