化工进展 ›› 2023, Vol. 42 ›› Issue (5): 2233-2244.DOI: 10.16085/j.issn.1000-6613.2022-1321

• 化工过程与装备 • 上一篇    下一篇

模拟移动床分离过程及其优化方法研究进展

凌山(), 刘聚明, 张前程, 李艳()   

  1. 内蒙古工业大学化工学院,内蒙古 呼和浩特 010000
  • 收稿日期:2022-07-14 修回日期:2022-09-12 出版日期:2023-05-10 发布日期:2023-06-02
  • 通讯作者: 李艳
  • 作者简介:凌山(1998—),男,硕士研究生,研究方向为化工分离过程。E-mail:lingshan_tian@139.com
  • 基金资助:
    国家自然科学基金(22268031);内蒙古自然科学基金(2021BS02003);内蒙古自治区关键技术攻关计划(2021GG0248);内蒙古工业大学科学研究项目(ZZ202001)

Research progress on simulated moving bed separation process and its optimization methods

LING Shan(), LIU Juming, ZHANG Qiancheng, LI Yan()   

  1. Chemical Engineering Institute, Inner Mongolia University of Technology, Hohhot 010000, Inner Mongolia, China
  • Received:2022-07-14 Revised:2022-09-12 Online:2023-05-10 Published:2023-06-02
  • Contact: LI Yan

摘要:

模拟移动床技术具有产率高、纯度高、过程连续性等优点,适用于多组分体系及各组分性质比较接近的难分离体系,其过程设计和优化工作一直是研究的重点和难点。本文首先对模拟移动床分离机理及其各种变型进行了介绍,其中重点阐述了目前应用广泛的顺序式模拟移动床技术的分离模式和优越性能。在此基础上,总结并分析了模拟移动床领域的各种优化方法和研究进展。从传统的三角形理论开始,总结归纳了三角形理论应用体系,指出其重要地位及局限性。之后依次介绍了基于三角形理论衍生而出的序列二次规划算法、应用较为广泛的驻波设计、体积分离分析和基于遗传算法的过程模拟、多目标优化等多种优化方法。分析结果表明,除多目标优化以外,无论是最传统的三角形理论,还是其他几种优化方法,在参数选择和实验设计等方面都存在诸多局限性,而多目标优化方法已被证明表现更为优异,可以适用于模拟移动床操作模式的各种变型,在未来将具有极大的发展潜力和应用前景。

关键词: 模拟移动床, 顺序式模拟移动床, 多目标优化, 遗传算法

Abstract:

The simulated moving bed technology has the advantages of high yield, high purity and process continuity, which makes it applicable for multi-component system and complicated system containing components with similar properties. However, the process design and optimization are always the important and challenging works for its research and application. In this paper, the separation mechanism and various modifications of simulated moving bed were firstly introduced, and then the widely used sequential simulated moving bed technology was emphatically described due to its unique separation mode and superior performance. Based on this background, diverse optimization methods and research progress of simulated moving bed area were summarized and analyzed. At first, the conventional triangle theory was investigated and its important applications and limitations were summarized. Furthermore, several optimization methods, such as sequence quadratic programming algorithm, standing wave design, separation volume analysis and multi-objective optimization method based on NSGA-Ⅱ algorithm were reviewed, respectively. The literature analysis revealed that in addition to multi-objective optimization, both the basic triangle theory and other optimization methods showed many limitations in parameter selection and experiment design. The multi-objective optimization method was proved to perform better and suitable for most simulated moving bed modes, which would have great development potential and application prospects in the future.

Key words: simulated moving bed, sequential simulated moving bed, multi-objective optimization, genetic algorithm

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