Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0098-1354(03)00159-5
DC FieldValue
dc.titleOptimization of reactive SMB and Varicol systems
dc.contributor.authorSubramani, H.J.
dc.contributor.authorHidajat, K.
dc.contributor.authorRay, A.K.
dc.date.accessioned2014-10-09T09:57:45Z
dc.date.available2014-10-09T09:57:45Z
dc.date.issued2003-12-15
dc.identifier.citationSubramani, H.J., Hidajat, K., Ray, A.K. (2003-12-15). Optimization of reactive SMB and Varicol systems. Computers and Chemical Engineering 27 (12) : 1883-1901. ScholarBank@NUS Repository. https://doi.org/10.1016/S0098-1354(03)00159-5
dc.identifier.issn00981354
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/92194
dc.description.abstractA comprehensive optimization study on a simulated moving bed reactor (SMBR) system is reported in this article for the direct synthesis of methyl tertiary butyl ether (MTBE) from tertiary butyl alcohol (TBA) and methanol. The applicability of the Varicol process, which is based on non-synchronous shift of the inlet and outlet ports, is explored for the first time for a reactive system. Multi-objective (two and three objective functions) optimization has been performed for both existing as well as design stage for SMBR and Varicol systems and their efficiencies are compared. The optimization problem involves relatively large number of decision variables; both continuous variables, such as flow rates in various sections and length of the columns and discrete variables, such as number of columns and column configuration. Pareto optimal solutions are obtained. It is observed that a five-column Varicol performs better than an equivalent five-column SMBR and its performance is nearly equal to that of a six-column SMBR in terms of purity and yield of MTBE and minimal eluent consumption. This is an important inference as it enables the reduction of fixed and operating costs while at the same time helps to achieve high purity and yield of the desired product and conversion of the limiting reactant. A state-of-the-art optimization technique, viz., non-dominated sorting genetic algorithm (NSGA), which allows handling of these complex optimization problems, is employed for this study. This is the first time that, not only the separating potential of Varicol has been extended to reaction systems, but also was optimized for multiple objectives. © 2003 Elsevier Ltd. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/S0098-1354(03)00159-5
dc.sourceScopus
dc.subjectGenetic algorithm
dc.subjectMTBE
dc.subjectMulti-objective optimization
dc.subjectPareto set
dc.subjectSimulated moving bed
dc.subjectVaricol
dc.typeArticle
dc.contributor.departmentCHEMICAL & ENVIRONMENTAL ENGINEERING
dc.description.doi10.1016/S0098-1354(03)00159-5
dc.description.sourcetitleComputers and Chemical Engineering
dc.description.volume27
dc.description.issue12
dc.description.page1883-1901
dc.description.codenCCEND
dc.identifier.isiut000186564200012
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