(300g) The Functionalities of Fast-Chrom/Smb (Fast and Accurate Simulation Tools for Chromatography and Smb)
Simulated Moving Bed (SMB) processes have emerged as a promising technology for the separation of not only conventional compounds, e.g., petro-chemicals and sugars, but also pharmaceuticals, e.g., chiral compounds, and bio-chemicals, e.g., amino acids, peptides and proteins (Lim, 2004). SMB chromatography usually works with the inherent advantage of a high driving force, resulting in less solvent consumption, smaller apparatus scale, lower investment costs and higher yields. However, in order to fully take advantage of this principle, a large number of operational parameters (e.g., flowrates, switching time, column dimension and configuration) need to be adjusted properly (Klatt et al., 2002). Since an experimental evaluation of these operational parameters is very time consuming and costly, model-based simulation and optimization can help to effectively search optimum operation conditions. This article presents the functionalities of a modeling, simulation and optimization tool for batch and simulated moving bed chromatography, so-called FAST-Chrom/SMB (Fast and Accurate Simulation Tools for Chromatography and SMB). This tool is able to perform i) model parameter estimation, ii) process simulation, and iii) optimization of operation conditions. The integrated tool deals with linear, Langmuir, modified Langmuir, polynomials, or user-defined models for adsorption isotherms, as well as, equilibrium, nonequilibrium linear driving force or nonequilibrium film-diffusion model for mass transfer mechanisms. Isocratic, linear or gradient salt mode is also realized. The feed flowrates (PowerFeed) and concentrations (ModiCon) can be modified within a cycle time for SMB operations. 4-zone SMB and multi-zone SMB processes can be simulated. The adsorption model described by partial differential equations (PDEs) is solved by the conservation element and solution element (CE/SE) method, which is recently developed by Chang (2004). Optimization algorithms such as SQP (successive quadratic programming) and GA (genetic algorithm) are included. The operating conditions of the SMB process are initialized by standing wave analysis or Triangle theory. The simulation results are visualized for the elution curve (time vs. concentration) in the batch chromatography and for the concentration profile w.r.t. the column length in the SMB. The SMB process performance (purity, yield, productivity, desorbent consumption) is given within the result file.
Keywords: batch chromatography, SMB chromatography, adsorption isotherms, modeling/simulation/optimization, adsorption process design.