Dynamic optimization of a novel radial-flow, spherical-bed methanol synthesis reactor in the presence of catalyst deactivation using Differential Evolution (DE) algorithm

In this work, a novel radial-flow spherical-bed methanol synthesis reactor has been optimized using Differential Evolution (DE) algorithm. This reactor's configuration visualizes the concentration and temperature distribution inside a radial-flow packed bed with a novel design for improving reactor performance with lower pressure drop. The dynamic simulation of spherical multi-stage reactors has been studied in the presence of long-term catalyst deactivation. A theoretical investigation has been performed in order to evaluate the optimal operating conditions and enhancement of methanol production in radial-flow spherical-bed methanol synthesis reactor. The simulation results have been shown that there are optimum values of the reactor inlet temperatures, profiles of temperatures along the reactors and reactor radius ratio to maximize the overall methanol production. The optimization methods have enhanced additional yield throughout 4 years of catalyst lifetime, respectively.