Development and Optimization of a Single Column Analog Model for a Multi-Column Counter-Current Solvent Gradient Purification Process

This contribution presents a modeling and optimization method for multi-column counter-current purification (MCSGP) processes. The model is based on conventional column models and by using the symmetric and cyclic steady state characteristics of the process a single column analog model was developed. The model have been used for dynamic optimization of the MCSGP process. The optimization was based on a simultaneous method where the control and state variables were discretized using a direct and local collocation method on finite elements in the temporal dimension and a finite volume weighted essentially non-oscillatory (WENO) scheme in the spatial dimension. The resulting nonlinear program (NLP) were solved using an interior point method.

The case study presented shows that the zero-order hold elution trajectories, developed for single column batch operation, can be extended to semi-continuous multi-column chromatography with product recycling. The optimization results is composed of a set of operating conditions where the product was upgraded to 95% purity with 99% process yield.