Dealing with Uncertainty in Polymer Manufacturing by Using Linear Regression Metrics and Sensitivity Analysis

Autores
Bojarski, Aarón David; Alvarez Medina, Carlos Rodrigo; Puigjaner, Luis
Año de publicación
2009
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In the polymers industry, models are heavily parameterizised, and the effect of each parameter on model outputs has not been extensively studied. A wide range of values for most of model's parameters can be found in literature [1], a thorough analysis regarding the model's sensitivity to the parameters' values is needed to find the set of parameters that have the most impact in the output results and consequently deserve an extra effort and care during their estimation. In this work, a global sensibility analysis of a styrene emulsion polymerization reactor model is carried out in order to determine the set of critical parameters.
Fil: Bojarski, Aarón David. Universidad Politécnica de Catalunya; España
Fil: Alvarez Medina, Carlos Rodrigo. Universidad Politécnica de Catalunya; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Puigjaner, Luis. Universidad Politécnica de Catalunya; España
Materia
Monte Carlo Sampling
Polymer Production Modelling
Regression Analysis
Sensitivity Analysis
Uncertainty
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/61649
Acceder
id CONICETDig_984c6d940ed2604bea87f013f422d88c
oai_identifier_str oai:ri.conicet.gov.ar:11336/61649
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Dealing with Uncertainty in Polymer Manufacturing by Using Linear Regression Metrics and Sensitivity AnalysisBojarski, Aarón DavidAlvarez Medina, Carlos RodrigoPuigjaner, LuisMonte Carlo SamplingPolymer Production ModellingRegression AnalysisSensitivity AnalysisUncertaintyhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2In the polymers industry, models are heavily parameterizised, and the effect of each parameter on model outputs has not been extensively studied. A wide range of values for most of model's parameters can be found in literature [1], a thorough analysis regarding the model's sensitivity to the parameters' values is needed to find the set of parameters that have the most impact in the output results and consequently deserve an extra effort and care during their estimation. In this work, a global sensibility analysis of a styrene emulsion polymerization reactor model is carried out in order to determine the set of critical parameters.Fil: Bojarski, Aarón David. Universidad Politécnica de Catalunya; EspañaFil: Alvarez Medina, Carlos Rodrigo. Universidad Politécnica de Catalunya; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Puigjaner, Luis. Universidad Politécnica de Catalunya; EspañaElsevier2009-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/61649Bojarski, Aarón David; Alvarez Medina, Carlos Rodrigo; Puigjaner, Luis; Dealing with Uncertainty in Polymer Manufacturing by Using Linear Regression Metrics and Sensitivity Analysis; Elsevier; Computer Aided Chemical Engineering; 26; 12-2009; 725-7301570-7946CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/S1570-7946(09)70121-Xinfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S157079460970121Xinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-02-26T10:04:34Zoai:ri.conicet.gov.ar:11336/61649instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982026-02-26 10:04:34.984CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Dealing with Uncertainty in Polymer Manufacturing by Using Linear Regression Metrics and Sensitivity Analysis
title Dealing with Uncertainty in Polymer Manufacturing by Using Linear Regression Metrics and Sensitivity Analysis
spellingShingle Dealing with Uncertainty in Polymer Manufacturing by Using Linear Regression Metrics and Sensitivity Analysis
Bojarski, Aarón David
Monte Carlo Sampling
Polymer Production Modelling
Regression Analysis
Sensitivity Analysis
Uncertainty
title_short Dealing with Uncertainty in Polymer Manufacturing by Using Linear Regression Metrics and Sensitivity Analysis
title_full Dealing with Uncertainty in Polymer Manufacturing by Using Linear Regression Metrics and Sensitivity Analysis
title_fullStr Dealing with Uncertainty in Polymer Manufacturing by Using Linear Regression Metrics and Sensitivity Analysis
title_full_unstemmed Dealing with Uncertainty in Polymer Manufacturing by Using Linear Regression Metrics and Sensitivity Analysis
title_sort Dealing with Uncertainty in Polymer Manufacturing by Using Linear Regression Metrics and Sensitivity Analysis
dc.creator.none.fl_str_mv Bojarski, Aarón David
Alvarez Medina, Carlos Rodrigo
Puigjaner, Luis
author Bojarski, Aarón David
author_facet Bojarski, Aarón David
Alvarez Medina, Carlos Rodrigo
Puigjaner, Luis
author_role author
author2 Alvarez Medina, Carlos Rodrigo
Puigjaner, Luis
author2_role author
author
dc.subject.none.fl_str_mv Monte Carlo Sampling
Polymer Production Modelling
Regression Analysis
Sensitivity Analysis
Uncertainty
topic Monte Carlo Sampling
Polymer Production Modelling
Regression Analysis
Sensitivity Analysis
Uncertainty
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv In the polymers industry, models are heavily parameterizised, and the effect of each parameter on model outputs has not been extensively studied. A wide range of values for most of model's parameters can be found in literature [1], a thorough analysis regarding the model's sensitivity to the parameters' values is needed to find the set of parameters that have the most impact in the output results and consequently deserve an extra effort and care during their estimation. In this work, a global sensibility analysis of a styrene emulsion polymerization reactor model is carried out in order to determine the set of critical parameters.
Fil: Bojarski, Aarón David. Universidad Politécnica de Catalunya; España
Fil: Alvarez Medina, Carlos Rodrigo. Universidad Politécnica de Catalunya; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Puigjaner, Luis. Universidad Politécnica de Catalunya; España
description In the polymers industry, models are heavily parameterizised, and the effect of each parameter on model outputs has not been extensively studied. A wide range of values for most of model's parameters can be found in literature [1], a thorough analysis regarding the model's sensitivity to the parameters' values is needed to find the set of parameters that have the most impact in the output results and consequently deserve an extra effort and care during their estimation. In this work, a global sensibility analysis of a styrene emulsion polymerization reactor model is carried out in order to determine the set of critical parameters.
publishDate 2009
dc.date.none.fl_str_mv 2009-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/61649
Bojarski, Aarón David; Alvarez Medina, Carlos Rodrigo; Puigjaner, Luis; Dealing with Uncertainty in Polymer Manufacturing by Using Linear Regression Metrics and Sensitivity Analysis; Elsevier; Computer Aided Chemical Engineering; 26; 12-2009; 725-730
1570-7946
CONICET Digital
CONICET
url http://hdl.handle.net/11336/61649
identifier_str_mv Bojarski, Aarón David; Alvarez Medina, Carlos Rodrigo; Puigjaner, Luis; Dealing with Uncertainty in Polymer Manufacturing by Using Linear Regression Metrics and Sensitivity Analysis; Elsevier; Computer Aided Chemical Engineering; 26; 12-2009; 725-730
1570-7946
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/S1570-7946(09)70121-X
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S157079460970121X
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1858305115412234240
score 13.176822

Publicaciones similares