Izvorni znanstveni članak
https://doi.org/10.15255/CABEQ.2021.1913
Modeling and Multi-objective Optimization of a Packed Bed Reactor for Sulfur Dioxide Removal by Magnesium Oxide Using Non-dominated Sorting Genetic Algorithm II
A. Bakhshi Ani
; Department of Chemical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
H. Ale Ebrahim
orcid.org/0000-0003-0947-9444
; Department of Chemical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
Sažetak
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.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Ključne riječi
SO2 removal; magnesium oxide; packed bed reactor; random pore model; modeling and simulation; multi-objective optimization
Hrčak ID:
264346
URI
Datum izdavanja:
20.10.2021.
Posjeta: 629 *