Parameter estimation for LLDPE gas-phase reactor models
Autor(a) principal: | |
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Data de Publicação: | 2007 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Brazilian Journal of Chemical Engineering |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322007000200011 |
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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Brazilian Journal of Chemical Engineering |
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Parameter estimation for LLDPE gas-phase reactor modelsEthylene polymerizationParameter estimationEmpirical modelPhenomenological modelLLDPEProduct 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.Brazilian Society of Chemical Engineering2007-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322007000200011Brazilian Journal of Chemical Engineering v.24 n.2 2007reponame:Brazilian Journal of Chemical Engineeringinstname:Associação Brasileira de Engenharia Química (ABEQ)instacron:ABEQ10.1590/S0104-66322007000200011info:eu-repo/semantics/openAccessNeumann,G. A.Finkler,T. F.Cardozo,N. S. M.Secchi,A. R.eng2007-07-23T00:00:00Zoai:scielo:S0104-66322007000200011Revistahttps://www.scielo.br/j/bjce/https://old.scielo.br/oai/scielo-oai.phprgiudici@usp.br||rgiudici@usp.br1678-43830104-6632opendoar:2007-07-23T00:00Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ)false |
dc.title.none.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,G. A. 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,G. A. |
author_facet |
Neumann,G. A. Finkler,T. F. Cardozo,N. S. M. Secchi,A. R. |
author_role |
author |
author2 |
Finkler,T. F. Cardozo,N. S. M. Secchi,A. R. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Neumann,G. A. Finkler,T. F. Cardozo,N. S. M. Secchi,A. R. |
dc.subject.por.fl_str_mv |
Ethylene polymerization Parameter estimation Empirical model Phenomenological model LLDPE |
topic |
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.none.fl_str_mv |
2007-06-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322007000200011 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322007000200011 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0104-66322007000200011 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Brazilian Society of Chemical Engineering |
publisher.none.fl_str_mv |
Brazilian Society of Chemical Engineering |
dc.source.none.fl_str_mv |
Brazilian Journal of Chemical Engineering v.24 n.2 2007 reponame:Brazilian Journal of Chemical Engineering instname:Associação Brasileira de Engenharia Química (ABEQ) instacron:ABEQ |
instname_str |
Associação Brasileira de Engenharia Química (ABEQ) |
instacron_str |
ABEQ |
institution |
ABEQ |
reponame_str |
Brazilian Journal of Chemical Engineering |
collection |
Brazilian Journal of Chemical Engineering |
repository.name.fl_str_mv |
Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ) |
repository.mail.fl_str_mv |
rgiudici@usp.br||rgiudici@usp.br |
_version_ |
1754213172301004800 |