Multi-objective optimization of supersonic separator for gas removal and carbon capture using three-field two-phase flow model and non-dominated sorting Genetic Algorithm-II (NSGA-II)
Hongbing Ding, Guangchen Zhang, Shiwei Wang, Yu Zhang, Yan Yang, Chuang Wen
Abstract
• A novel gas–liquid three-field two-phase CFD model was established. • The effects of geometry parameters were investigated to get structural sensitivity. • Multi-objective optimization of supersonic separator structure based on CFD model. • At a 90% separation efficiency, the pressure loss ratio was reduced by up to 28.3%. • Optimized structures suitable for primary and secondary separation were found. Supersonic separator (SS) is an efficient technology used for gas removal and carbon capture. To enhance its performance, many researchers have studied its structure; however, existing studies have primarily used traditional CFD models for single-objective structural optimization of the separator’s separation performance. However, in the SS, separation efficiency and pressure-loss ratio are the most important and conflicting performance parameters, and evaluating separation performance in isolation from either one is incomplete. Therefore, in this paper, a gas–liquid two-phase three-field CFD model considering a liquid film is firstly established, and then this model is combined with the non-dominated Sorting Genetic Algorithm-II (NSGA-II) for multi-objective optimization of the coupled multiple structural parameters with the objective of the separation efficiency and pressure-loss ratio. The results indicated that the maximum relative errors between simulated and predicted values for the four Pareto optimal solutions in computing pressure loss ratio and separation efficiency are 5.4% and 5.3%, respectively, with these solutions achieving the maximum reduction in pressure loss ratio of 28.3% at the same 90% separation efficiency compared to the original structure.