On simplified modelling approaches to SMB processes

Grosfils, Valérie; Levrie, C.; Kinnaert, Michel; Wouwer, Alain Vande

doi:10.1016/j.compchemeng.2006.06.003

Cited by 6 publications

(4 citation statements)

References 11 publications

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“…The components in a SMB plant move through the column as nonlinear waves (Helfferich and Carr, 1993;Grosfils et al, 2007a). Two fronts per component can be identified in the concentration profiles; see Fig.…”

Section: The Wave Theory In Smbmentioning

confidence: 99%

Combination of multi-model predictive control and the wave theory for the control of simulated moving bed plants

Vilas¹,

Wouwer²

2011

Chemical Engineering Science

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Section: The Wave Theory In Smbmentioning

confidence: 99%

Combination of multi-model predictive control and the wave theory for the control of simulated moving bed plants

Vilas¹,

Wouwer²

2011

Chemical Engineering Science

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Section: Process Simulationmentioning

confidence: 99%

“…A number of approaches have been taken to analyze or simulate SMB process schemes including the use of true moving bed approximations 14,33 and standing-wave models. 29,33 In our work, we utilized a standard lumped-parameter linear driving force rate-based model. 14,20,21,34,35 With this approach, the material balance for component i in column j, in terms of mass per unit volume, is given by…”

Section: Process Simulationmentioning

confidence: 99%

SMB chromatography design using profile advancement factors, miniplant data, and rate‐based process simulation

et al. 2009

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This article describes a systematic miniplant-based approach to rapid development of simulated moving bed (SMB) chromatography applications. The methodology involves analysis of single-column pulse tests to screen adsorbents and operating conditions and to determine initial values of profile advancement factors used to specify flow rates for an initial SMB miniplant experiment. A lumped-parameter linear driving force rate-based model is developed by fitting process data from a single miniplant run. The data are fit in a two-step procedure involving initial determination of effective adsorption isotherm constants as best-fit parameters with subsequent adjustment of calculated mass transfer coefficients to refine the data fit. The resulting simulation is used to guide further miniplant work and minimize experimental effort. The methodology is illustrated with miniplant data for a binary protein separation showing excellent agreement between model results and process data generated over a wide range of operating conditions.

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“…Mathematical modeling is a key means to SMB study. − The SMB operation can be well simulated by a proper model if the overall mass transfer coefficients, axial dispersion coefficients, and adsorption isotherms could be accurately estimated in advance. This work adopts the model used extensively by several authors, − and the model parameters are given in Table .…”

Section: Parameters Of Model Simulationmentioning

confidence: 99%

Modeling Comparison between Novel and Traditional Feed Modes of Simulated Moving Bed

and

Zhao

2008

Ind. Eng. Chem. Res.

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A new feed mode for simulated moving bed (SMB) is proposed. The solution out of zone II flows into a tank to dissolve the solid raw materials and is then fed into zone III. The feasibility of the new feed mode was examined with a model SMB operation. The results showed that this mode could effectively separate mixtures. As the raw materials are dissolved with the solution from zone II, the solvent consumption is reduced significantly in comparsion with the traditional SMB operations; whereas the productivities and purities change insignificantly. When the flow rates of raffinate and extract stream are similar, the concentration plateaus of two solutes in column have similar and suitable heights, otherwise an overly high concentration could cause the solutes to be crystalized and plug the column. The volume of solution tank showed an insignificant effect on the separation. Increasing the tank volume can make a smooth change of concentrations of solutes in the tank, which is beneficial to the operation.

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On simplified modelling approaches to SMB processes

Cited by 6 publications

References 11 publications

Combination of multi-model predictive control and the wave theory for the control of simulated moving bed plants

Combination of multi-model predictive control and the wave theory for the control of simulated moving bed plants

SMB chromatography design using profile advancement factors, miniplant data, and rate‐based process simulation

Modeling Comparison between Novel and Traditional Feed Modes of Simulated Moving Bed

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