Simulation and multi-objective optimization of a radial flow gas-cooled membrane reactor, considering reduction of CO2 emissions in methanol synthesis

This paper deals with a steady-state simulation of a Radial Flow Gas-Cooled Reactor (RF-GCR) and a Radial Flow Gas-Cooled Membrane Reactor (RF-GCMR) for enhancing CO2 removal in the methanol synthesis process. Reactors consist of annular packed-beds (subsections) and annular cooling-chambers. This configuration creates radial flows for reacting and synthesis gases and results in a negligible pressure drop along the beds. Each subsection is in contact with two cooling-chambers from top and bottom that offers an excellent heat transfer area and contributes to a noteworthy reduction in reaction phase temperature. Besides, hydrogen permeation through Pd–Ag membrane layer in upper and lower walls of RF-GCMR cooling-chambers shifts the reaction toward more products. Simultaneous effects of pressure, temperature, and H2 permeation increases CO2 removal and methanol production rates by 592% and 6.84%, respectively in RF-GCMR compared to Conventional Gas-Cooled Reactor (CGCR). Afterward, a two-objective optimization of RF-GCMR is implemented using Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to maximize methanol production rate and selectivity. Final Pareto-optimal solution is found by TOPSIS, LINMAP, and Shannon’s Entropy decision-making methods. Shannon’s Entropy, with the lowest deviation index, improves CO2 removal and methanol production rates 78.3% and 10.77%, respectively in Optimized RF-GCMR (ORF-GCMR) compared to non-optimized RF-GCMR. [Display omitted] •Steady-state simulation of a Radial Flow Gas-Cooled Membrane Reactor (RF-GCMR).•An excellent heat transfer area and a negligible pressure drop in novel reactor.•A remarkable reduction in CO2 emissions of RF-GCMR through using Pd-Ag membrane.•Multi-objective optimization of RF-GCMR using NSGA-II algorithm.•The highest CO2 removal rate in optimized RF-GCMR through Shannon’s Entropy method.