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Received October 31, 2003
Accepted February 16, 2004
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This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits
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An Optimization Strategy for Nonlinear Simulated Moving Bed Chromatography: Multi-Level Optimization Procedure (MLOP)
Department of Chemical Engineering, Hankyong National University, 67 Sukjung-dong, Anseong-si, Kyonggi-do 456-749, Korea
Korean Journal of Chemical Engineering, July 2004, 21(4), 836-852(17), 10.1007/BF02705529
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Abstract
This paper presents a multi-level optimization strategy to obtain optimum operating conditions (four flowrates and cycle time) of nonlinear simulated moving bed chromatography. The multi-level optimization procedure (MLOP) approaches systematically from initialization to optimization with two objective functions (productivity and desorbent consumption), employing the standing wave analysis, the true moving bed (TMB) model and the simulated moving bed (SMB) model. The procedure is constructed on a non-worse solution property advancing level by level and its solution does not mean a global optimum. That is, the lower desorbent consumption under the higher productivity is successively obtained on the basis of the SMB model, as the two SMB-model optimizations are repeated by using a standard SQP (successive quadratic programming) algorithm. This approach takes advantage of the TMB model as well as surmounts shortcomings of the TMB model in the general case of any nonlinear adsorption isotherm using the SMB model. The MLOP is evaluated on two nonlinear SMB cases characterized by i) quasi-linear/nonequilibrium and ii) nonlinear/nonequilibrium model. For the two cases, the MLOP yields a satisfactory solution for high productivity and low desorbent consumption within required purities.
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References
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Biressi G, Ludemann-Hombourger O, Mazzotti M, Nicoud RM, Morbidelli M, J. Chromatogr. A, 876, 3 (2000)
Chang SC, "Courant Number Insensitive CE/SE Schemes," 38th AIAA Joint Propulsion Conference, AIAA-2002-3890, Indianapolis, USA (2002)
Juza M, Mazzotti M, Morbidelli M, Trends Biotechnol., 18, 108 (2000)
Kim YD, Lee JK, Cho YS, Korean J. Chem. Eng., 18(6), 971 (2001)
Klatt KU, Dunnebier G, Hanisch F, Engell S, AIChE Symp. Ser., 98, 239 (2002)
Lee KN, Korean J. Chem. Eng., 20(3), 532 (2003)
LimYI, Chang CS, Jorgensen SB, Comput. Chem. Eng., in press (2004)
Lim YI, Jorgensen SB, Chem. Eng. Sci., in press (2004)
Lim YI, Floquet P, Joulia X, Kim SD, Ind. Eng. Chem. Res., 38(12), 4729 (1999)
Ludemann-Hombourger O, Pigorini G, Nicoud RM, Ross DS, Terfloth G, J. Chromatogr. A, 947, 59 (2002)
Ma Z, Wang NH, AIChE J., 43(10), 2488 (1997)
Mazzotti M, Storti G, Morbidelli M, J. Chromatogr. A, 769, 3 (1997)
Melis S, Markos J, Cao G, Morbidelli M, Ind. Eng. Chem. Res., 35(10), 3629 (1996)
Motz S, Mitrovic A, Gilles ED, Chem. Eng. Sci., 57(20), 4329 (2002)
Pais LS, Loureiro JM, Rodrigues AE, Sep. Purif. Technol., 20, 67 (2000)
Pais LS, Loureiro JM, Rodrigues AE, AIChE J., 44(3), 561 (1998)
Powell MJD, J. Inst. Math. Appl., 7, 21 (1971)
Proll T, Kusters E, J. Chromatogr. A, 800, 135 (1998)
Strube J, Altenboner U, Meurer M, J. Chromatogr. A, 769, 81 (1997)
Wu DJ, Ma Z, Wang NHL, J. Chromatogr. A, 855, 71 (1999)
Xie Y, Wu DJ, Ma ZD, Wang NHL, Ind. Eng. Chem. Res., 39(6), 1993 (2000)
Zhang ZY, Hidajat K, Ray AK, Morbidelli M, AIChE J., 48(12), 2800 (2002)
Zhang Z, Mazzotti M, Morbidelli M, J. Chromatogr. A, 989, 95 (2003)
