模拟移动床反应器中合成乙酸甲酯过程的多目标优化

Multi-Objective Optimization of Methyl Acetate Synthesis in a Simulated Moving Bed Reactor

采用非支配基因算法(Non-dominated Sorting Genetic Algorithm,NSGA-II)对模拟移动床反应器(SimulatedMoving Bed Reactor,SMBR)中合成乙酸甲酯(MeOAc)过程进行了多目标优化。所考虑的优化问题包括:(a)MeOAc产率和纯度同时最大化;(b)产率最大化和洗脱剂用量最小化;(c)产率、纯度的最大化和洗脱剂用量最小化。以MeOAc产率和纯度最大化为目标,确定了5柱SMBR最优的各区柱数分布和乙酸进料摩尔分率。此外,还研究了转化率限制和洗脱液流量对多目标优化非劣解(Pareto optimal solutions)的影响。提出并验证了一种SMBR设计和优化的通用方法。

The multi-objective optimization of a simulated moving bed reactor（SMBR） for the synthesis of methyl acetate（MeOAc） was performed by using Non-dominated Sorting Genetic Algorithm（NSGA-II）.The optimization problems solved are（a） simultaneous maximization of productivity and purity of MeOAc,（b） simultaneous maximization of productivity of MeOAc and minimization of desorbent consumption,and（c） simultaneous maximization of productivity and purity of MeOAc together with minimization of desorbent consumption.The optimal configuration of a 5-column SMBR unit and the optimal acetic acid feed mole fraction in terms of maximum productivity and purity of MeOAc were determined.The effects of conversion constraint and eluent flow rate on the Pareto optimal solutions were also investigated.Some important SMBR features that have been established under ideal conditions were explained in details.This work provides and validates a general approach towards the optimal design and operation of SMBR processes.