dc.creatorPolic, AL
dc.creatorLona, LMF
dc.creatorDuever, TA
dc.creatorPenlidis, A
dc.date2004
dc.dateFEB 23
dc.date2014-11-17T01:49:20Z
dc.date2015-11-26T16:35:09Z
dc.date2014-11-17T01:49:20Z
dc.date2015-11-26T16:35:09Z
dc.date.accessioned2018-03-28T23:17:33Z
dc.date.available2018-03-28T23:17:33Z
dc.identifierMacromolecular Theory And Simulations. Wiley-blackwell, v. 13, n. 2, n. 115, n. 132, 2004.
dc.identifier1022-1344
dc.identifierWOS:000220056800002
dc.identifier10.1002/mats.200300015
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/53639
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/53639
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/53639
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1271421
dc.descriptionAs our understanding of chemical processes increases, the complexity of the models developed to describe them also increases. In most cases the equations are nonlinear in the inputs and parameters, and must be solved numerically. At present in estimating parameters for large process models, there are two shortcomings in the existing knowledge about (multiresponse) parameter estimation. The first is, how effective is the present parameter estimation methodology when applied to large models, and the second is, can any advantage be gained from considering the parameter estimation problem as a whole. This paper will address these questions, by revisiting the various steps of a parameter estimation protocol. There is little discussion in the literature as to how all the steps for parameter estimation are related. In the development of this protocol all of the steps for parameter estimation will be revisited: parameter sensitivity analysis, statistical design of experiments, estimation of parameters and confidence regions. By considering all these steps as a whole the overall parameter estimation procedure can be more efficient and some pitfalls, such as local optima and incorrect confidence regions, may be dealt with in an appropriate manner. To illustrate the application of the protocol, two case studies related to polymerization models are presented. These case studies illustrate some of the problems that may be encountered in the parameter estimation process and how the proposed protocol can aid in overcoming them.
dc.description13
dc.description2
dc.description115
dc.description132
dc.languageen
dc.publisherWiley-blackwell
dc.publisherMalden
dc.publisherEUA
dc.relationMacromolecular Theory And Simulations
dc.relationMacromol. Theory Simul.
dc.rightsfechado
dc.rightshttp://olabout.wiley.com/WileyCDA/Section/id-406071.html
dc.sourceWeb of Science
dc.subjectcomputer modeling
dc.subjectconfidence intervals
dc.subjectparameter estimation
dc.subjectsensitivity analysis
dc.subjectsimulations
dc.subjectDesign
dc.subjectSituations
dc.subjectPackage
dc.titleA protocol for the estimation of parameters in process models: Case studies with polymerization scenarios
dc.typeArtículos de revistas


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