Optimizing VPSA technology of methane purification from natural gas based on Aspen Adsorption model and response surface analysis

• A self-customized hydrothermally treated wheat flour porous carbon foam (HWPCF) is developed for efficient CH 4 purification from natural gas. • A powerful framework combining Aspen Adsorption simulation with Response Surface Methodology (RSM) is established for VPSA process optimization. • The mechanisms of pressure-regulated adsorption separation and the heavy components dominated thermal front are elucidated. • Multi-objective optimization identifies key operating parameters, achieving an exceptional CH 4 purity of 99.996 % with a recovery rate of 56.482 %. • The study provides a validated and robust strategy for guiding the scale-up and industrial design of efficient VPSA processes. Methane (CH 4 ) purification is essential for the safe and efficient high-pressure pipeline transportation of natural gas. This study employed self-customized hydrothermally treated wheat flour porous carbon foam (HWPCF) for the high-efficiency purification of CH 4 from natural gas using a vacuum pressure swing adsorption (VPSA) process. The mixture gas of CH 4 /C 2 H 6 /C 3 H 8 (0.85/0.10/0.05) was set according to the conventional component of natural gas and the separation of HWPCF for the mixture gas was evaluated under varying feed pressures based on adsorption breakthrough experiments combined with simulation. Concurrently, temperature variation and heat effect within the adsorption bed were investigated. This combined approaches both Aspen Adsorption model and response surface methodology (RSM) for VPSA process were employed to evaluate the impact of three key operating factors (adsorption pressure, desorption pressure, and adsorption time) on CH 4 purity and recovery rate. By multi-objective optimization, the optimal parameters were adsorption/desorption pressures of 6.783 bar/0.251 bar, and an adsorption time of 222.66 s, which enabled the VPSA process to achieve a CH 4 purity of 99.996 % and a recovery rate of 56.482 %. The results demonstrate the significant role of integrating Aspen Adsorption simulation with RSM in both investigating the internal adsorption mechanism and guiding the industrial design.