Please use this identifier to cite or link to this item: http://repositorio.unitau.br/jspui/handle/20.500.11874/2640
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGuimaraes, O. L. C.pt_BR
dc.contributor.authorSilva, M. B.pt_BR
dc.date.accessioned2019-09-12T16:53:34Z-
dc.date.available2019-09-12T16:53:34Z-
dc.date.issued2007-
dc.citation.volume46pt_BR
dc.citation.issue1pt_BR
dc.citation.spage45-
dc.citation.epage51-
dc.identifier.doi10.1016/j.cep.2006.04.005pt_BR
dc.identifier.issn0255-2701-
dc.identifier.issn1873-3204-
dc.identifier.urihttp://repositorio.unitau.br/jspui/handle/20.500.11874/2640-
dc.description.abstractThe purpose of this work is to obtain a neural model of the Acid Brown 75, Acid Orange 52, Acid Orange 10 and Direct Red 28 dyes decoloration process. Dyes aqueous solutions were individually treated in plug-flow reactor, with ultraviolet radiation and hydrogen peroxide. The decoloration process was evaluated in function of the absorbance reading in each dye maximum absorbance wavelength. The input variables corresponding to the input neurons of the neural feedforward backpropagation model used in the work were comprised by structural parameters characteristic of each dye (number of azo bonds and sulphonate groups) and also by process operational variables (temperature, initial pH, hydrogen peroxide volume, reactor operation time and dyes concentration). The combination of structural and operational parameters provided a hybrid character in relation to the input variable nature. The correlation coefficients (approximately 0.96 for the data total, validation and test sets) showed the good model prediction capacity. The neural model obtained also provided, via Garson Partition Method, the determination of the influence of the decoloration process input variables. (c) 2006 Elsevier B.V. All rights reserved.en
dc.description.provenanceMade available in DSpace on 2019-09-12T16:53:34Z (GMT). No. of bitstreams: 0 Previous issue date: 2007en
dc.languageInglêspt_BR
dc.publisherElsevier Science Sa-
dc.publisher.countrySuíçapt_BR
dc.relation.ispartofChemical Engineering and Processing-Process Intensification-
dc.rightsEm verificaçãopt_BR
dc.sourceWeb of Sciencept_BR
dc.subject.otherNeural Networken
dc.subject.otherDecolorationen
dc.subject.otherAzo Dyesen
dc.subject.otherH2o2/Uv Decolorationen
dc.subject.otherNetworksen
dc.subject.otherPhotodegradationen
dc.titleHybrid neural model for decoloration by UV/H2O2 involving process variables and structural parameters characteristics to azo dyesen
dc.typeArtigo de Periódicopt_BR
dc.contributor.orcidSilva, Messias Borges https://orcid.org/0000-0002-8656-0791pt_BR
dc.contributor.researcheridSilva, Messias Borges/F-5959-2012pt_BR
dc.identifier.wosWOS:000242518300006-
dc.description.affiliationFac Engn Quim Lorena, BR-12608970 Rodovia Itajuba, Lorena, Brazil; Universidade de Taubaté (Unitau), BR-12020040 Taubate, SP, Brazil-
dc.subject.wosareaEnergy & Fuelsen
dc.subject.wosareaEngineering, Chemicalen
dc.subject.researchareaEnergy & Fuelsen
dc.subject.researchareaEngineeringen
Appears in Collections:Artigos de Periódicos

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.