Process Analysis And System Optimization Of Simulated Moving Bed Chromatography

Simulated moving bed chromatography, the main representative of continuous chromatography, is widely used in petrochemical industry, sugar industry, fine chemicals, chiral separation of drugs and other fields. With the increasing complexity of industrial processes and larger scale of production, people put higher demand on the economic benefits of the production process. The traditional production target which focused on smooth operation can not meet the requirements now. Optimization of production process facilities to improve product quality and reduce energy consumption, has become an important technological innovation study of technology workers and enterprises.In this paper, the research work of simulated moving bed chromatography is carried out from mathematical model, simulation platform development and system operation parameters optimization, and computer simulation, system design guide and operating parameters optimization have been achieved. In this way, it can guide the production process, improve product quality and productivity. Our ultimate target is to save energy, accelerate the promotion of simulated moving bed technology, and improve the competitiveness of enterprises.The main contents of this paper are as following:Firstly, SMB(Simulated Moving Bed) and TMB(True Moving Bed) models are establish based on simulated moving bed chromatography modeling methods and modeling theory; Numerical method to solve the model equations are implemented; Study on SMB chromatography startup process and periodic steady-state are carried out; performance indicators and the average concentration distribution of SMB and TMB models are compared. At last, the fact that TMB model can be used for multi-objective optimization is demonstrated.Secondly, according to the requirement of simulated moving bed chromatography in scientific research and practical application, a simulated moving bed chromatography analysis platform is developed. This analysis platform can not only realize SMB chromatographic process computer simulation, but also can be used to take comprehensive and systematic studies on the influence of operational parameters and the bed structures on separation performance indicators. Meanwhile, discussions of SMB chromatographic process using the software are taken out in this paper.Finally, a preference-based non-dominated sorting genetic algorithm (PNSGA) and NSGA-II algorithm (elitist non-dominated sorting genetic algorithm) are used in simulated moving bed chromatography multi-objective optimization with different targets. The research shows that, due to the introduction of preference targets, PSNGA algorithm will use preference information to guide the search direction, and its final optimized results not only have better performance indicators, but also meet the target requirements. This optimization method is particularly applicable to strict separation requirements field such as fine chemicals and chiral separation.