Multi-objective optimization of industrial membrane SMR to produce syngas for Fischer-Tropsch production using NSGA-II and decision makings

Abstract Membrane reactors are an advanced technology with vast application capacities for equilibrium limited endothermic reactions. The main propose of this study is to offer an optimized packed-bed membrane steam methane reforming (SMR) tubular reactor for sustainable CH 4 conversion by implementing triple-objective optimization model based on optimum H 2 /CO ratio for low temperature Fischer-Tropsch (F-T) process. In this study a one dimensional pseudo-homogeneous model based on mass, energy, and momentum conservation laws is used to simulate the behavior of a packed-bed membrane reactor for production of syngas by SMR. In the optimization section, the proposed work explores optimal values of various decision variables that simultaneously maximize CH 4 conversion, H 2 selectivity, and CO selectivity by applying elitist non-dominated sorting genetic algorithm (NSGA-II). Pareto optimal frontier between triple objectives is obtained in three spaces and best optimal value is selected by using LINMAP, TOPSIS, Shannon's entropy and Fuzzy Bellman-Zadeh decision making methods. The final optimal solutions illustrate that the membrane reactor presents higher CH 4 conversion which can be operated under milder conditions than the conventional reactor.

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