Conceptual Approach in Multi-Objective Optimization of Packed Bed Membrane Reactor for Ethylene Epoxidation Using Real-coded Non-Dominating Sorting Genetic Algorithm NSGA-II
Abstract An isothermal plug flow reactor model with extended Fick diffusion model for transport through the porous membrane is utilized for simulation of ethylene oxide formation in a packed bed membrane reactor (PBMR). The model was verified and validated using published experimental data from an existing lab-scale unit. Sensitivity analysis was performed to determine robustness of the model. A conceptual approach on operation and design stage multi-objective optimization study is discussed. Real-coded NSGA-II is used and effect of its parameters on optimization of reactor performance is also studied. The results of three two-objective operation-stage (with 4 decision variables) and one two-objective design-stage (with 6 decision variables) optimization case studies are presented. Good convergence to a Pareto optimal solution is achieved for all cases. Significant improvement over current experimental operation is observed in terms of increase in conversion of ethylene, selectivity to ethylene oxide and ethylene oxide product flow rate.