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This paper presents a novel optimization and design strategy for simulated moving bed (SMB) chromatographic processes in general and SMB reactors in particular. A suitable computationally efficient and accurate process model is presented. The choice of the process model is motivated by a brief review on modeling and simulation of SMB processes. A review on design strategies for SMB processes, their capabilities, and limitations is given, which is limited to pure separation processes since no rigorous design and optimization approach for SMB reactors has been published so far. The novel optimization strategy is based on mathematical optimization, a rigorous dynamic process model, and a detailed cost function. The desired properties of the novel optimization approach are derived from the limitations of the currently known design strategies. The capabilities of the new approach are illustrated using two applications of the SMB chromatographic reactor. Potential savings in operating cost of up to 20% and in desorbent consumption of up to 60% are identified.

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