Combination of genetic algorithm and CFD modelling to develop a new model for reliable prediction of normal shock wave in supersonic flows contributing to carbon capture

Carbon dioxide separation and capture using green efficient methods is an important issue in studies related to climate change. The supersonic separator one of the reliable that can be used separate impurities, including carbon dioxide, from gas streams. Reliable estimation normal shock wave position plays a vital role proper design simulation separators. Many have one-dimensional theoretical (ideal) model for pressure recovery, but accuracy ideal may insufficient some situations, as reported literature. A novel approach presented this paper provide new equations waves by combination computational fluid dynamics (CFD) genetic algorithm. comparison proposed with several experimental data indicate present provides more accurate predictions than traditional wave. showed average absolute relative deviation (AARD) 1.80%, which about six times less AARD model, indicating robustness model. Consequently, employed tool prediction converging–diverging nozzles.