Dynamics of a True Moving Bed separation process: Effect of operating variables on performance indicators using orthogonalization method

Abstract The assessment of the performance of cyclic adsorption systems is usually addressed in literature in terms of steady state. To reach further developments in this field, the characterization of the dynamic behavior of the processes becomes necessary. This work focus on the application of a method based on Gram-Schmidt Orthogonalization to analyze the impact of the operating variables in the dynamic response of a TMB unit. Another objective of this work is to characterize the dynamic system behavior and compare it with the orthogonalization method results. The results showed that the recycling flow rate is the operating variable with the greatest impact for the system considered. The step perturbation analysis showed the consistence of the proposed method and that some process variables result in a system inverse response for the recovery performance indicator. The importance of taking in consideration the process dynamics in the unit design, control and optimization is demonstrated.

[1]  David W. Bacon,et al.  Modeling Ethylene/Butene Copolymerization with Multi‐site Catalysts: Parameter Estimability and Experimental Design , 2003 .

[2]  Luís S. Pais,et al.  Modeling strategies for enantiomers separation by SMB chromatography , 1998 .

[3]  Manfred Morari,et al.  Optimizing control of simulated moving beds--linear isotherm. , 2004, Journal of chromatography. A.

[4]  Pedro Sá Gomes,et al.  Chiral separation of flurbiprofen enantiomers by preparative and simulated moving bed chromatography. , 2011, Chirality.

[5]  Alírio E. Rodrigues,et al.  Simulated moving‐bed reactor: Reactive–separation regions , 2005 .

[6]  Andreas Seidel-Morgenstern,et al.  Analysis and Demonstration of a Control Concept for a Heat Integrated Simulated Moving Bed Reactor , 2011 .

[7]  Alírio E. Rodrigues,et al.  Separation of chiral mixtures in real SMB units: The FlexSMB-LSRE® , 2009 .

[8]  Mark A. Stadtherr,et al.  Rigorous Global Optimization for Dynamic Systems Subject to Inequality Path Constraints , 2011 .

[9]  Brahim Benyahia,et al.  Emulsion copolymerization of styrene and butyl acrylate in the presence of a chain transfer agent. Part 2: parameters estimability and confidence regions , 2013 .

[10]  Luís S. Pais,et al.  Separation of 1,1'-bi-2-naphthol enantiomers by continuous chromatography in simulated moving bed , 1997 .

[11]  Alírio E. Rodrigues,et al.  Fructose–glucose separation in a SMB pilot unit: Modeling, simulation, design, and operation , 2001 .

[12]  Alírio E. Rodrigues,et al.  Simulated Moving Bed Chromatography: From Concept to Proof‐of‐Concept , 2012 .

[13]  Achim Kienle,et al.  A simple robust control for simulated moving bed chromatographic separation , 2012 .

[14]  Martin Mönnigmann,et al.  Systematic identifiability testing for unambiguous mechanistic modeling – application to JAK-STAT, MAP kinase, and NF-κB signaling pathway models , 2009, BMC Systems Biology.

[15]  Manfred Morari,et al.  Automatic Control of Simulated Moving Beds II: Nonlinear Isotherm , 2004 .

[16]  Costas Kravaris,et al.  Advances and selected recent developments in state and parameter estimation , 2013, Comput. Chem. Eng..

[17]  Luís S. Pais,et al.  Chiral separation by SMB chromatography , 2000 .

[18]  Nuno S. Graça,et al.  Simulated Moving Bed Technology: Principles, Design and Process Applications , 2015 .

[19]  Bjarne A. Foss,et al.  Parameter ranking by orthogonalization - Applied to nonlinear mechanistic models , 2008, Autom..

[20]  Marco Mazzotti,et al.  Identification and predictive control of a simulated moving bed process: Purity control , 2006 .

[21]  Manfred Morari,et al.  Experimental implementation of automatic 'cycle to cycle' control of a chiral simulated moving bed separation. , 2007, Journal of chromatography. A.

[22]  Celina Pinto Leão,et al.  Transient and steady-state models for simulated moving bed processes: numerical solutions , 2004, Comput. Chem. Eng..

[23]  Sebastian Engell,et al.  Optimization-based control of a reactive simulated moving bed process for glucose isomerization , 2004 .

[24]  Achim Kienle,et al.  Design of simulated moving bed processes under reduced purity requirements. , 2007, Journal of chromatography. A.

[25]  Hans Bock,et al.  Efficient optimization of simulated moving bed processes , 2007 .

[26]  Karsten-Ulrich Klatt,et al.  Model-based control of a simulated moving bed chromatographic process for the separation of fructose and glucose , 2002 .

[27]  Massimo Morbidelli,et al.  Continuous chromatographic separation through simulated moving beds under linear and nonlinear conditions , 1998 .

[28]  Lorenz T. Biegler,et al.  Modeling and optimization of a seeded suspension polymerization process , 2010 .

[29]  Yoshiaki Kawajiri,et al.  Systematic optimization and experimental validation of ternary simulated moving bed chromatography systems. , 2014, Journal of chromatography. A.

[30]  Jungmin Oh,et al.  Optimization of reactive simulated moving bed systems with modulation of feed concentration for production of glycol ether ester. , 2014, Journal of chromatography. A.

[31]  Paul Richert,et al.  Applications of simulated moving-bed chromatography to the separation of the enantiomers of chiral drugs , 1997 .

[32]  Luís S. Pais,et al.  Cyclic steady state of simulated moving bed processes for enantiomers separation , 2003 .

[33]  Liulin Cao,et al.  Gray-box modeling and control of polymer molecular weight distribution using orthogonal polynomial neural networks , 2012 .