The VariCol process is a variant of the conventional simulated moving bed (SMB) process, distinguished by the asynchronous shifting of the inlet and outlet ports of the chromatographic column train. This feature allows for a more flexible operation in column utilization and can also achieve higher separation performances. However, to take full benefit out of it, the operating parameters, such as the strategy for port switching, must be optimal. in this paper, a novel methodology for optimizing those parameters, based on a single NLP (non-linear programming), is proposed. The main advantage of this approach is that it significantly reduces the complexity of the original MINLP (mixed-integer non-linear programming) formulation currently discussed in the literature. The proposed optimization problem is built, considering that the average column configuration of three zones provides the necessary and sufficient information to describe the VariCol process. Several optimization scenarios for the enantioseparation of 1,1´-bi-2-naphthol and aminoglutethimide were considered to evaluate the proposed methodology and to compare the performance of VariCol and SMB processes. The results have shown that with the single NLP approach, it is possible to explore the optimal solution in all the VariCol process domains with less computational effort than other optimization strategies reported in the literature. That is a great advantage, especially in the context of real-time applications.
Keywords: Column Configuration; Enantioseparation; SMB Optimization; Simulated Moving Bed; VariCol Process; shifting scheme.
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