Multi-objective optimization for helium-heated reverse water gas shift reactor by using NSGA-II

Abstract

Thermodynamic performance of helium-heated reverse water gas shift (RWGS) reactor is investigated by using the theory of finite-time thermodynamics. Taking into account both the radial temperature gradients and the diffusion-reaction phenomenon inside the catalytic pellets, a comprehensive two-dimensional pseudo-homogeneous mathematical model is established to represent the reactor. By using numerical calculations, the thermodynamic performance of reactors in the given conditions is analyzed, the influences of the effective parameters on reactor performance are also examined. Eventually, from the perspective of heat management and production improvement, a multi-objective optimization (MOO) procedure based on the non-dominated sorting genetic algorithm (NSGA-II) is applied to investigate the best working parameters considering the minimum radial temperature difference and maximum conversion rate as optimization objective functions. The results show that significant radial temperature gradients and the resulting radial gradients of apparent reaction rate can be observed. The thermodynamic performance of the counter-flow reactor is superior to that of the parallel-flow pattern. The MOO is an effective technique for selecting the best working parameters to reduce the radial temperature difference and improve the conversion rate simultaneously.