(470e) Modeling Simulated Moving Bed Processes Via the General Rate Model Under Nonlinear Conditions

Chromatography is a highly selective process of separation which is often employed in the separation of complex mixtures. Conventional preparative elution chromatography is a batch process. As opposed to conventional batch chromatography continuous chromatographic separation processes, have gained greater interest in the last decades due to its advantages in terms of productivity and eluent consumption. The simulated moving bed (SMB) technology is an important technique for large-scale continuous chromatographic separation processes especially when the initial mixture contains only two components. This technology has been applied over four decades in the petrochemical industry and currently enjoying preparative an production scale separation of sugars, proteins, pharmaceuticals, fine chemicals, flavorings, foods and enantiomers. Because of its complex nature of operation, generally a model-based control scheme is used so as to obtain a stable and better understood SMB process. Thus a great deal of theoretical work has been carried out for developing useful simulation procedures for design and process development purposes. There are several models to be used for chromatographic separations whether it is at the analytical scale or at the preparative/production scale, including the ideal model, the equilibrium dispersive model, the transport dispersive model and the general rate (GR) model. The GR model is widely acknowledged as being the most comprehensive among the chromatography models available in the literature as it accounts for axial dispersion and all the mass transfer resistances, e.g. external mass transfer of solute molecules from bulk phase to the external surface of the adsorbent, diffusion of the solute molecules through the particle, and adsorption-desorption processes on the site of the particles. The solution of the GR model based SMB governing equations involves the employment of advanced numerical techniques that requires considerable machine time. Therefore the GR model is seldom employed in modeling studies of SMB processes [1-2], and according to the best of our knowledge, only under linear isotherm conditions. For homogeneous diffusion, Özdural et al. [3] proposed a new algorithm for numerical solution of the GR model in chromatographic columns. The advantage of this methodology lays in the fact that it does not require the solution of coupled partial differential equations; instead the stationary phase concentrations were evaluated through unsteady state component mass balance expressions written in discretization schemes. Thus the number of partial differential equations to be solved reduces to one and the computation time significantly lessens. In this study this technique is extended to SMB systems and applied to two component Langmuir type nonlinear isotherms in SMB separation systems. Thus a sophisticated chromatography model, i.e. the GR model, is employed in SMB simulation studies under nonlinear conditions. The solution of the present model predicts the concentration profiles of the two components along the columns and the concentration histories at the raffinate and the extract ports. Use of this new methodology allows us to suggest protocols for SMB system operation parameters and/or facilitate scale-up procedures.

References [1] Dünnebier G., Weirich I., Klatt, K.-U. (1998) Computationally efficient dynamic modelling and simulation of simulated moving bed chromatographic processes with linear isotherms. Chemical Engineering Science, 53: 253-2546. [2] Cremasco M. A., Starquit A., Wang N.-H.L. (2009) Separation of l-tryptophan present in an aromatic amino acids mixture in a four-column simulated moving bed: Experimental and simulation studies. Brazilian Journal of Chemical Engineering, 26: 611-618. [3] Özdural A.R., Alkan A., Kerkhof P.A.J.M. (2004) Modeling chromatographic columns: Non-equilibrium packed-bed adsorption with non-linear adsorption isotherms. Journal of Chromatography A, 1041: 77-85.