Parameter estimation for LLDPE gas-phase reactor models

Detalhes bibliográficos
Autor(a) principal: Neumann, Gustavo Alberto
Data de Publicação: 2007
Outros Autores: Finkler, Tiago Fiorenzano, Cardozo, Nilo Sérgio Medeiros, Secchi, Argimiro Resende
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/30508
Resumo: Product development and advanced control applications require models with good predictive capability. However, in some cases it is not possible to obtain good quality phenomenological models due to the lack of data or the presence of important unmeasured effects. The use of empirical models requires less investment in modeling, but implies the need for larger amounts of experimental data to generate models with good predictive capability. In this work, nonlinear phenomenological and empirical models were compared with respect to their capability to predict the melt index and polymer yield of a low-density polyethylene production process consisting of two fluidized bed reactors connected in series. To adjust the phenomenological model, the optimization algorithms based on the flexible polyhedron method of Nelder and Mead showed the best efficiency. To adjust the empirical model, the PLS model was more appropriate for polymer yield, and the melt index needed more nonlinearity like the QPLS models. In the comparison between these two types of models better results were obtained for the empirical models.
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spelling Neumann, Gustavo AlbertoFinkler, Tiago FiorenzanoCardozo, Nilo Sérgio MedeirosSecchi, Argimiro Resende2011-08-04T06:00:54Z20070104-6632http://hdl.handle.net/10183/30508000595702Product development and advanced control applications require models with good predictive capability. However, in some cases it is not possible to obtain good quality phenomenological models due to the lack of data or the presence of important unmeasured effects. The use of empirical models requires less investment in modeling, but implies the need for larger amounts of experimental data to generate models with good predictive capability. In this work, nonlinear phenomenological and empirical models were compared with respect to their capability to predict the melt index and polymer yield of a low-density polyethylene production process consisting of two fluidized bed reactors connected in series. To adjust the phenomenological model, the optimization algorithms based on the flexible polyhedron method of Nelder and Mead showed the best efficiency. To adjust the empirical model, the PLS model was more appropriate for polymer yield, and the melt index needed more nonlinearity like the QPLS models. In the comparison between these two types of models better results were obtained for the empirical models.application/pdfengBrazilian journal of chemical engineering. São Paulo, SP. Vol. 24, no. 2 (Apr./Jun. 2007), p.267-275Polietileno de baixa densidadeProcessos químicos : ModelagemPolimerizaçãoEthylene polymerizationParameter estimationEmpirical modelPhenomenological modelLLDPEParameter estimation for LLDPE gas-phase reactor modelsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/otherinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSORIGINAL000595702.pdf000595702.pdfTexto completo (inglês)application/pdf318701http://www.lume.ufrgs.br/bitstream/10183/30508/1/000595702.pdf51ee3185fe375de6b212adec4099ae53MD51TEXT000595702.pdf.txt000595702.pdf.txtExtracted Texttext/plain20892http://www.lume.ufrgs.br/bitstream/10183/30508/2/000595702.pdf.txt3b4a2263c55c4c77a28f11d4881d3384MD52THUMBNAIL000595702.pdf.jpg000595702.pdf.jpgGenerated Thumbnailimage/jpeg1959http://www.lume.ufrgs.br/bitstream/10183/30508/3/000595702.pdf.jpg8b24267e6a6567cd2662d50e5af278caMD5310183/305082023-04-17 03:27:58.034065oai:www.lume.ufrgs.br:10183/30508Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-04-17T06:27:58Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv Parameter estimation for LLDPE gas-phase reactor models
title Parameter estimation for LLDPE gas-phase reactor models
spellingShingle Parameter estimation for LLDPE gas-phase reactor models
Neumann, Gustavo Alberto
Polietileno de baixa densidade
Processos químicos : Modelagem
Polimerização
Ethylene polymerization
Parameter estimation
Empirical model
Phenomenological model
LLDPE
title_short Parameter estimation for LLDPE gas-phase reactor models
title_full Parameter estimation for LLDPE gas-phase reactor models
title_fullStr Parameter estimation for LLDPE gas-phase reactor models
title_full_unstemmed Parameter estimation for LLDPE gas-phase reactor models
title_sort Parameter estimation for LLDPE gas-phase reactor models
author Neumann, Gustavo Alberto
author_facet Neumann, Gustavo Alberto
Finkler, Tiago Fiorenzano
Cardozo, Nilo Sérgio Medeiros
Secchi, Argimiro Resende
author_role author
author2 Finkler, Tiago Fiorenzano
Cardozo, Nilo Sérgio Medeiros
Secchi, Argimiro Resende
author2_role author
author
author
dc.contributor.author.fl_str_mv Neumann, Gustavo Alberto
Finkler, Tiago Fiorenzano
Cardozo, Nilo Sérgio Medeiros
Secchi, Argimiro Resende
dc.subject.por.fl_str_mv Polietileno de baixa densidade
Processos químicos : Modelagem
Polimerização
topic Polietileno de baixa densidade
Processos químicos : Modelagem
Polimerização
Ethylene polymerization
Parameter estimation
Empirical model
Phenomenological model
LLDPE
dc.subject.eng.fl_str_mv Ethylene polymerization
Parameter estimation
Empirical model
Phenomenological model
LLDPE
description Product development and advanced control applications require models with good predictive capability. However, in some cases it is not possible to obtain good quality phenomenological models due to the lack of data or the presence of important unmeasured effects. The use of empirical models requires less investment in modeling, but implies the need for larger amounts of experimental data to generate models with good predictive capability. In this work, nonlinear phenomenological and empirical models were compared with respect to their capability to predict the melt index and polymer yield of a low-density polyethylene production process consisting of two fluidized bed reactors connected in series. To adjust the phenomenological model, the optimization algorithms based on the flexible polyhedron method of Nelder and Mead showed the best efficiency. To adjust the empirical model, the PLS model was more appropriate for polymer yield, and the melt index needed more nonlinearity like the QPLS models. In the comparison between these two types of models better results were obtained for the empirical models.
publishDate 2007
dc.date.issued.fl_str_mv 2007
dc.date.accessioned.fl_str_mv 2011-08-04T06:00:54Z
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10183/30508
dc.identifier.issn.pt_BR.fl_str_mv 0104-6632
dc.identifier.nrb.pt_BR.fl_str_mv 000595702
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url http://hdl.handle.net/10183/30508
dc.language.iso.fl_str_mv eng
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dc.relation.ispartof.pt_BR.fl_str_mv Brazilian journal of chemical engineering. São Paulo, SP. Vol. 24, no. 2 (Apr./Jun. 2007), p.267-275
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