LAPSE:2021.0310
Published Article
LAPSE:2021.0310
Efficient Simulation of Chromatographic Processes Using the Conservation Element/Solution Element Method
April 30, 2021
Chromatographic separation processes need efficient simulation methods, especially for nonlinear adsorption isotherms such as the Langmuir isotherms which imply the formation of concentration shocks. The focus of this paper is on the space−time conservation element/solution element (CE/SE) method. This is an explicit method for the solution of systems of partial differential equations. Numerical stability of this method is guaranteed when the Courant−Friedrichs−Lewy condition is satisfied. To investigate the accuracy and efficiency of this method, it is compared with the classical cell model, which corresponds to a first-order finite volume discretization using a method of lines approach (MOL). The evaluation is done for different models, including the ideal equilibrium model and a mass transfer model for different adsorption isotherms—including linear and nonlinear Langmuir isotherms—and for different chromatographic processes from single-column operation to more sophisticated simulated moving bed (SMB) processes for the separation of binary and ternary mixtures. The results clearly show that CE/SE outperforms MOL in terms of computational times for all considered cases, ranging from 11-fold for the case with linear isotherm to 350-fold for the most complicated case with ternary center-cut eight-zone SMB with Langmuir isotherms, and it could be successfully applied for the optimization and control studies of such processes.
Keywords
conservation element/solution element (CE/SE) method, method of lines (MOL), simulated moving bed (SMB) chromatography, Simulation, single-column chromatography
Suggested Citation
Chernev VP, Vande Wouwer A, Kienle A. Efficient Simulation of Chromatographic Processes Using the Conservation Element/Solution Element Method. (2021). LAPSE:2021.0310
Author Affiliations
Chernev VP: Institut für Automatisierungstechnik, Otto von Guericke University, Universitätsplatz 2, 39106 Magdeburg, Germany [ORCID]
Vande Wouwer A: Systems, Estimation, Control and Optimization (SECO), University of Mons, 31 Boulevard Dolez, 7000 Mons, Belgium [ORCID]
Kienle A: Institut für Automatisierungstechnik, Otto von Guericke University, Universitätsplatz 2, 39106 Magdeburg, Germany; Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstraße 1, 39106 Magdeburg, Germany
Journal Name
Processes
Volume
8
Issue
10
Article Number
E1316
Year
2020
Publication Date
2020-10-20
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr8101316, Publication Type: Journal Article
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LAPSE:2021.0310
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doi:10.3390/pr8101316
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Apr 30, 2021
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Apr 30, 2021
 
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Calvin Tsay
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