Cryogenic Process Optimization for Natural Gas Purification: Predictive Modeling of Methane-CO₂ Solid-Vapor Phase Equilibrium Using Response Surface Methodology

This research combines industrial engineering principles with chemical process modeling to explore the capture of CO₂ from natural gas under cryogenic conditions. The study specifically investigates the Solid-Vapor (S-V) phase equilibrium in a methane-carbon dioxide (CH₄-CO₂) system. The study employs Response Surface Methodology (RSM) to develop a robust model for predicting phase behavior in industrial gas separation processes. The model is validated using experimental data, offering enhanced operational insights into cryogenic CO₂ capture in industrial applications. The developed RSM model is particularly valuable as it can predict the mole fractions of methane and CO₂ at various temperatures and pressures in the solid-vapor region of phase equilibrium, where limited experimental data make it difficult to estimate these components accurately. The key contribution of this study is to validate the RSM model’s available experimental data, and the model can further be used to predict the process conditions at which high methane composition (yCH₄) can be achieved. The developed model showed good agreement when the results were compared with previous experimental studies. The utilization of chemical engineering data to forecast previously unknown conditions in gas separation processes broadens the scope of industrial process optimization in this work.