Modeling and Multi-objective Optimization of a Packed Bed Reactor for Sulfur Dioxide Removal by Magnesium Oxide Using Non-dominated Sorting Genetic Algorithm II

Abstract

Nowadays, protecting the environment is of utmost importance worldwide, and sulfur dioxide is one of the main pollutants in the atmosphere. This work proposes a new method for simultaneous SO2 removal by MgO, and production of magnesium sulfate in a packed bed reactor for which breakthrough curves have been obtained. Furthermore, the effect of important operating parameters, including temperature, SO2 concentration, and gaseous flow rate was investigated. Experiments showed that increasing the temperature improved the breakthrough lifetime, but the increase in concentration and flow rate reduced the lifetime. The experimental results were predicted successfully by applying the Random Pore Model (RPM). Finally, the Non-dominated Sorting Genetic Algorithm II (NSGA II) that is a technique for multi-objective optimization, was employed to determine the best operating parameters for SO2 removal by magnesium oxide in the packed bed reactor.