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A heuristic approach for the economic optimization of a series of CSTR's performing michaelis–menten reactions

dc.contributor.authorMalcata, F. Xavier
dc.date.accessioned2011-10-21T12:08:13Z
dc.date.available2011-10-21T12:08:13Z
dc.date.issued1989
dc.description.abstractThe estimation of the size of each reactor of a series of CSTR's performing a Michaelis–Menten reaction in the liquid phase can be obtained to advantage via an optimization technique leading to the minimum overall capital cost. The cost scaleup is assumed to be described by a power rule on the equipment capacity. Various contributions are lumped into the exponent, thus leading to values above unity. The analytical development leading to the optimal intermediate concentrations of substrate according to the foregoing criterion is presented. A short-cut method based on an empirical expression that approximates the numerical solution is reported. This correlation is found to be exact at the asymptotic behaviors, and to give accurate results within an acceptable error level for the range with physical interest. Therefore, it is particularly useful during the predesign steps of equipment for the biochemical industry.por
dc.identifier.citationMALCATA, F. Xavier - A heuristic approach for the economic optimization of a series of CSTR's performing michaelis–menten reactions. Biotechnology and Bioengineering. ISSN 0006-3592. Vol. 33 n.º 3 (1989), p. 251-255por
dc.identifier.doi10.1002/bit.260330302
dc.identifier.eid84988073239
dc.identifier.urihttp://hdl.handle.net/10400.14/6652
dc.identifier.wosA1989R628700001
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherWileypor
dc.titleA heuristic approach for the economic optimization of a series of CSTR's performing michaelis–menten reactionspor
dc.typejournal article
dspace.entity.typePublication
person.familyNameMalcata
person.givenNameFrancisco
person.identifier.ciencia-id1B13-38A5-35F5
person.identifier.orcid0000-0003-3073-1659
person.identifier.scopus-author-id7102542478
rcaap.rightsrestrictedAccesspor
rcaap.typearticlepor
relation.isAuthorOfPublicationa06c00da-0e2f-4434-8ede-4d7b22c0dfe9
relation.isAuthorOfPublication.latestForDiscoverya06c00da-0e2f-4434-8ede-4d7b22c0dfe9

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