顺序式模拟移动床分离低聚木糖多目标优化及其变量调控机制

Multi-objective optimization of sequentially-simulated moving bed for separation of xylo-oligosaccharides and its variables regulation mechanism

在前期分离实验基础上,采用非支配排序遗传算法(non-dominated sorting genetic algorithmⅡ,NSGA-Ⅱ)对顺序式模拟移动床(sequential simulated moving bed reactor, SSMB)分离低聚木糖的过程进行了多目标优化,重点研究了SSMB分离过程的最佳操作区间及其变量调控机制,并与传统的模拟移动床进行了对比,在此基础之上提出了一种具有普适性的变量控制策略。以低聚木糖产品收率最大化和水耗最小化为目标,详细分析了SSMB分离过程的最优操作曲线、变量变化趋势、内部浓度曲线和出口处质量流量,提出了一种适用于SSMB的设计优化和变量调控的通用策略,证明了不能用传统的流量比及平衡理论来对SSMB过程进行变量控制,为SSMB在糖类多组分体系、结构复杂的手性药物及生物质体系的应用提供了新思路和新方法。

Based on the previous separation experiments, non-dominated sorting genetic algorithm Ⅱ is employed to perform multi-objective optimization on xylo-oligosaccharides(XOS) separation process by sequential simulated moving bed(SSMB).The optimum operating conditions and variables regulation mechanism for SSMB separation process are studied, and compared with those for traditional simulated moving bed.Based on the study conclusion, a universal variables control strategy is proposed.Aiming at maximizing the yield of xylo-oligosaccharides and minimizing the water consumption, the optimal operation curve, variation trend of variables, internal concentration curve and mass flow rate at the outlet of SSMB separation process are analyzed in detail.Finally, a universal strategy suitable for design optimization and variables regulation of SSMB is proposed, and it is proved that traditional flow ratio and balance theory cannot be used for variables control of SSMB process.It also provides a new idea and method for the application of SSMB in the carbohydrate multi-component system, complex chiral drugs, and biomass systems.