Multi-objective optimization for catalytic methane decomposition in fixed-bed reactors-a computational approach

This study established a numerical model for transient catalytic methane decomposition (CMD). The carbon formation kinetics was modeled based on the experimental data. Using the established numerical model, it was found that higher feed methane concentration and volume flow rate increased the maximum carbon formation rates but decreased the methane conversion. It was also found that lower feed methane concentration enhanced methane conversion but reduced the maximum carbon formation rate. Based on the results predicted from the numerical model, a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm with Gaussian mutation was adopted to carry out the optimization for two objective functions (methane conversion and maximum carbon formation rate) and two decision variables (feed methane concentration and space velocity). With its advanced stochastic search and Gaussian mutation techniques, MOPSO effectively explores the solution space for excellent performance. The optimized scenarios from the Pareto optimal front were chosen for comparative evaluation to derive the optimal configuration. Maximizing the methane conversion and carbon formation rate illustrates a critical trade-off. The results show that for a reaction temperature of 550°C, the maximum methane conversion of 49% and maximum carbon formation rate of 12.5 g/gcat h can be obtained.