Abstract:
This study explores the optimization of membrane reactor configurations to enhance hydrogen production
through CH4 tri-reforming. The investigation employs ceramic membranes for oxygen, vapor, and carbon dioxide
distribution within the reactor bed. A differential evolution algorithm is utilized alongside cuckoo search algorithm (CSA) and support vector regression (SVR) to determine optimal values for O2/CH4, H2O/CH4, and CO2/
CH4 ratios, membrane thickness, and shell pressure, with hydrogen yield as the objective function. Results
demonstrate that the oxygen membrane reactor achieves the highest hydrogen yield, reaching 2.02 and 1.75 for
direct methanol synthesis and Fischer–Tropsch processes, respectively, representing a 7.98 % and 10.03 % increase compared to the conventional tri-reforming reactor. Furthermore, CSA and SVR emerge as invaluable
tools, facilitating robust optimization and predictive modeling. The CSA efficiently navigates complex solution
spaces to identify optimal parameters, while SVR accurately models relationships between input variables and
hydrogen yield. Incorporating these methodologies enhances the effectiveness of membrane reactor design and
synthesis gas production. This study contributes to advancements in clean energy technologies by providing
insights into efficient hydrogen production methods using membrane reactors.
