dc.creatorFernandes, FAN
dc.creatorLona, LMF
dc.date2002
dc.date2014-11-16T06:16:09Z
dc.date2015-11-26T16:20:30Z
dc.date2014-11-16T06:16:09Z
dc.date2015-11-26T16:20:30Z
dc.date.accessioned2018-03-28T23:02:55Z
dc.date.available2018-03-28T23:02:55Z
dc.identifierPolymer Reaction Engineering. Marcel Dekker Inc, v. 10, n. 3, n. 181, n. 192, 2002.
dc.identifier1054-3414
dc.identifierWOS:000178113300004
dc.identifier10.1081/PRE-120014695
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/54762
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/54762
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/54762
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1267824
dc.descriptionThe development of polymer resins can benefit from the application of neural networks. The aim of this paper is to present how neural networks can help deal with the development of new resins, starting from the end user properties to set up the reactor's operating conditions. The procedure presented in this paper consists of a network that predicts the operating conditions of the reactor with maximum error of 2%. New resins can be developed and the reactor's operating conditions can be set in a much faster way, reducing the number of experiments and pilot plant tests, and hence, time and money spent on development.
dc.description10
dc.description3
dc.description181
dc.description192
dc.languageen
dc.publisherMarcel Dekker Inc
dc.publisherNew York
dc.publisherEUA
dc.relationPolymer Reaction Engineering
dc.relationPolym. React. Eng.
dc.rightsfechado
dc.sourceWeb of Science
dc.subjectneural network
dc.subjectgas phase reactor
dc.subjectpolyethylene
dc.subjectfluidized bed reactor
dc.subjectpolymerization
dc.subjectIndustrial
dc.titleApplication of neural networks for the definition of the operating conditions of fluidized bed polymerization reactors
dc.typeArtículos de revistas


Este ítem pertenece a la siguiente institución