Parameter estimation for LLDPE gas-phase reactor models
Autor(a) principal: | |
---|---|
Data de Publicação: | 2007 |
Outros Autores: | , , |
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. |
id |
UFRGS-2_4fb70f09122d5b28b0af89db0d82ca33 |
---|---|
oai_identifier_str |
oai:www.lume.ufrgs.br:10183/30508 |
network_acronym_str |
UFRGS-2 |
network_name_str |
Repositório Institucional da UFRGS |
repository_id_str |
|
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 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/other |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
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 |
identifier_str_mv |
0104-6632 000595702 |
url |
http://hdl.handle.net/10183/30508 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFRGS instname:Universidade Federal do Rio Grande do Sul (UFRGS) instacron:UFRGS |
instname_str |
Universidade Federal do Rio Grande do Sul (UFRGS) |
instacron_str |
UFRGS |
institution |
UFRGS |
reponame_str |
Repositório Institucional da UFRGS |
collection |
Repositório Institucional da UFRGS |
bitstream.url.fl_str_mv |
http://www.lume.ufrgs.br/bitstream/10183/30508/1/000595702.pdf http://www.lume.ufrgs.br/bitstream/10183/30508/2/000595702.pdf.txt http://www.lume.ufrgs.br/bitstream/10183/30508/3/000595702.pdf.jpg |
bitstream.checksum.fl_str_mv |
51ee3185fe375de6b212adec4099ae53 3b4a2263c55c4c77a28f11d4881d3384 8b24267e6a6567cd2662d50e5af278ca |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS) |
repository.mail.fl_str_mv |
|
_version_ |
1801224728952700928 |