Optimization strategies for simulated moving bed and PowerFeed processes

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Abstract

Simulated moving bed (SMB) processes have been applied to many important separations in sugar, petrochemical, and pharmaceutical industries. However, systematic optimization of SMB is still a challenging problem. Two tailored approaches are proposed, full discretization and single discretization, where both the optimal operating condition and concentration profiles are obtained by a Newton-type solver. In a case study of fructose and glucose separation, it has been found that the full-discretization method implemented on AMPL with IPOPT is more efficient than single-discretization method on gPROMS with SRQPD. The reliability of the full-discretization method is also demonstrated with case studies of a bi-Langmuir isotherm and a PowerFeed optimization problem. © 2005 American Institute of Chemical Engineers AIChE J, 2006

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