General optimization strategy of simulated moving bed units through design of experiments and response surface methodologies

•A simple simulated moving bed optimization strategy based on DoE and RSM is proposed.•This approach is compared with Triangle Theory and the concept of separation volume.•The new DoE-RSM strategy provides accurate results with small number of simulations.•SMB separation of trans-stilbene oxide enan...

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Bibliographic Details
Published inComputers & chemical engineering Vol. 90; pp. 161 - 170
Main Authors Aniceto, José P.S., Cardoso, Simão P., Silva, Carlos M.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 12.07.2016
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Summary:•A simple simulated moving bed optimization strategy based on DoE and RSM is proposed.•This approach is compared with Triangle Theory and the concept of separation volume.•The new DoE-RSM strategy provides accurate results with small number of simulations.•SMB separation of trans-stilbene oxide enantiomers is used as a case study.•The proposed optimization strategy allowed purities above 99.6% for both enantiomers. The optimization of simulated moving bed (SMB) units is often performed through detailed phenomenological models and require extensive computation time. Hence several optimization methods like the Triangle Theory, and the concept of separation volume have been proposed. However, they do not provide accurate results, when mass transfer limitations are significant, or require a large number of simulations. In this work, a combined Design of Experiments and Response Surface Methodology (DoE-RSM) approach is proposed for SMB optimization, aimed at providing good results with simplicity and reduced number of simulations. The separation of trans-stilbene oxide enantiomers is selected as case study in order to compare DoE-RSM with previous approaches. In the whole, accurate results are obtained with a few number of simulations, allowing for purities above 99.60% for both enantiomers, and productivity of 65.41kg/(m3adsorbentday). The versatility of DoE-RSM tool is also discussed, emphasising their advantages and general applicability.
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ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2016.04.028