Mathematical modeling and optimization of industrial scale ELUXYL simulated moving bed (SMB)

摘要

In this work, a detailed study on the modeling, simulation and optimization of the industrial-scale Eluxyl simulated moving bed (SMB) process are presented. Commercial SPX3000 (Ba-faujasite type zeolite) was used as an adsorbent, and para-diethylbenzene applied as a desorbent for separating para-xylene from other C-8 aromatics isomers. In the first step, the xylenes and para-diethylbenzene adsorption equilibrium on the commercial adsorbent were measured at operating conditions (175 degrees C, 9 bar) experimentally. The density of particle and porosities were determined from commercial plant operation and adsorbent analysis. Furthermore, mass transfer coefficients, including internal (diffusion in the pore) and external (diffusion in the liquid film) resistance, have been investigated in details. A common mathematical model encompassing the SMB strategy, node model, extended Langmuir isotherm, and rate expression were constructed to implement a numerical simulation of the industrial-scale Eluxyl SMB process with and without considering backwash stream. The accuracy of the mathematical model was validated by the industrial data. Besides, a dynamic optimization framework with Sequential Quadratic Programming (SQP) optimization algorithm was used for obtaining optimal conditions. Two separate single objective optimizations by considering minimum desorbent consumption and maximum SMB unit productivity as objectives were firstly designated. By comparing the results, it was concluded that minimizing desorbent consumption was more favorable to be selected as an objective function, which could achieve 6.35% increase in productivity and 7.28% decrease in desorbent consumption. Finally, two-level optimization was planned for reaching maximum feed throughput with minimum desorbent consumption. The results showed that productivity could be increased by 13.75%, and para-diethylbenzene consumption could be reduced by 10.81% at the optimal condition.