Modelling the phase behavior of alkane mixtures in wide ranges of conditions: New parameterization and predictive correlations of binary interactions for the RKPR EOS

Autores
Cismondi Duarte, Martín; Cruz Doblas, J.; Gomez, M. J.; Montoya, Gerardo Federico
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
After showing in a previous publication a clear superiority to the classic Peng-Robinson EoS for the description of high pressure phase behavior in the more asymmetric alkane-alkane binary mixtures, in this work the RKPR EoS is turned into a predictive model by developing correlations of interaction parameters for all possible pairs or normal alkanes, associated also to a new parameterization of pure compounds. The proposed correlations are based on van der Waals quadratic mixing rules. Repulsive interaction lij parameters are implemented in all cases, while attractive kij interactions were necessary only for the methane-series and the more asymmetric systems of propane, in particular with carbon numbers higher than 24. The analysis of the results, in comparison to an important diversity of data available for several dozens of systems, demonstrates a very good predictive power for the new correlations, which could be useful in modeling the phase behavior of different hydrocarbon fluids.
Fil: Cismondi Duarte, Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (I). Grupo Vinculado al Plapiqui - Investigación y Desarrollo en Tecnología Química; Argentina. Universidad Nacional de Córdoba. Incubadora de Empresas; Argentina
Fil: Cruz Doblas, J.. Universidad Nacional de Córdoba. Incubadora de Empresas; Argentina
Fil: Gomez, M. J.. Universidad Nacional de Córdoba. Incubadora de Empresas; Argentina
Fil: Montoya, Gerardo Federico. Universidad Nacional de Córdoba. Incubadora de Empresas; Argentina
Materia
Critical Lines
High Pressure Phase Behavior
Hydrocarbons
Interaction Parameters Correlation
Rkpr
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:11336/43792
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Modelling the phase behavior of alkane mixtures in wide ranges of conditions: New parameterization and predictive correlations of binary interactions for the RKPR EOSCismondi Duarte, MartínCruz Doblas, J.Gomez, M. J.Montoya, Gerardo FedericoCritical LinesHigh Pressure Phase BehaviorHydrocarbonsInteraction Parameters CorrelationRkprhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2After showing in a previous publication a clear superiority to the classic Peng-Robinson EoS for the description of high pressure phase behavior in the more asymmetric alkane-alkane binary mixtures, in this work the RKPR EoS is turned into a predictive model by developing correlations of interaction parameters for all possible pairs or normal alkanes, associated also to a new parameterization of pure compounds. The proposed correlations are based on van der Waals quadratic mixing rules. Repulsive interaction lij parameters are implemented in all cases, while attractive kij interactions were necessary only for the methane-series and the more asymmetric systems of propane, in particular with carbon numbers higher than 24. The analysis of the results, in comparison to an important diversity of data available for several dozens of systems, demonstrates a very good predictive power for the new correlations, which could be useful in modeling the phase behavior of different hydrocarbon fluids.Fil: Cismondi Duarte, Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (I). Grupo Vinculado al Plapiqui - Investigación y Desarrollo en Tecnología Química; Argentina. Universidad Nacional de Córdoba. Incubadora de Empresas; ArgentinaFil: Cruz Doblas, J.. Universidad Nacional de Córdoba. Incubadora de Empresas; ArgentinaFil: Gomez, M. J.. Universidad Nacional de Córdoba. Incubadora de Empresas; ArgentinaFil: Montoya, Gerardo Federico. Universidad Nacional de Córdoba. Incubadora de Empresas; ArgentinaElsevier Science2015-10-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/43792Cismondi Duarte, Martín; Cruz Doblas, J.; Gomez, M. J.; Montoya, Gerardo Federico; Modelling the phase behavior of alkane mixtures in wide ranges of conditions: New parameterization and predictive correlations of binary interactions for the RKPR EOS; Elsevier Science; Fluid Phase Equilibria; 403; 15-10-2015; 49-590378-3812CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.fluid.2015.06.005info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0378381215003246?via%3Dihubinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T12:05:09Zoai:ri.conicet.gov.ar:11336/43792instacron: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:34982025-10-22 12:05:10.132CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Modelling the phase behavior of alkane mixtures in wide ranges of conditions: New parameterization and predictive correlations of binary interactions for the RKPR EOS
title Modelling the phase behavior of alkane mixtures in wide ranges of conditions: New parameterization and predictive correlations of binary interactions for the RKPR EOS
spellingShingle Modelling the phase behavior of alkane mixtures in wide ranges of conditions: New parameterization and predictive correlations of binary interactions for the RKPR EOS
Cismondi Duarte, Martín
Critical Lines
High Pressure Phase Behavior
Hydrocarbons
Interaction Parameters Correlation
Rkpr
title_short Modelling the phase behavior of alkane mixtures in wide ranges of conditions: New parameterization and predictive correlations of binary interactions for the RKPR EOS
title_full Modelling the phase behavior of alkane mixtures in wide ranges of conditions: New parameterization and predictive correlations of binary interactions for the RKPR EOS
title_fullStr Modelling the phase behavior of alkane mixtures in wide ranges of conditions: New parameterization and predictive correlations of binary interactions for the RKPR EOS
title_full_unstemmed Modelling the phase behavior of alkane mixtures in wide ranges of conditions: New parameterization and predictive correlations of binary interactions for the RKPR EOS
title_sort Modelling the phase behavior of alkane mixtures in wide ranges of conditions: New parameterization and predictive correlations of binary interactions for the RKPR EOS
dc.creator.none.fl_str_mv Cismondi Duarte, Martín
Cruz Doblas, J.
Gomez, M. J.
Montoya, Gerardo Federico
author Cismondi Duarte, Martín
author_facet Cismondi Duarte, Martín
Cruz Doblas, J.
Gomez, M. J.
Montoya, Gerardo Federico
author_role author
author2 Cruz Doblas, J.
Gomez, M. J.
Montoya, Gerardo Federico
author2_role author
author
author
dc.subject.none.fl_str_mv Critical Lines
High Pressure Phase Behavior
Hydrocarbons
Interaction Parameters Correlation
Rkpr
topic Critical Lines
High Pressure Phase Behavior
Hydrocarbons
Interaction Parameters Correlation
Rkpr
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv After showing in a previous publication a clear superiority to the classic Peng-Robinson EoS for the description of high pressure phase behavior in the more asymmetric alkane-alkane binary mixtures, in this work the RKPR EoS is turned into a predictive model by developing correlations of interaction parameters for all possible pairs or normal alkanes, associated also to a new parameterization of pure compounds. The proposed correlations are based on van der Waals quadratic mixing rules. Repulsive interaction lij parameters are implemented in all cases, while attractive kij interactions were necessary only for the methane-series and the more asymmetric systems of propane, in particular with carbon numbers higher than 24. The analysis of the results, in comparison to an important diversity of data available for several dozens of systems, demonstrates a very good predictive power for the new correlations, which could be useful in modeling the phase behavior of different hydrocarbon fluids.
Fil: Cismondi Duarte, Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (I). Grupo Vinculado al Plapiqui - Investigación y Desarrollo en Tecnología Química; Argentina. Universidad Nacional de Córdoba. Incubadora de Empresas; Argentina
Fil: Cruz Doblas, J.. Universidad Nacional de Córdoba. Incubadora de Empresas; Argentina
Fil: Gomez, M. J.. Universidad Nacional de Córdoba. Incubadora de Empresas; Argentina
Fil: Montoya, Gerardo Federico. Universidad Nacional de Córdoba. Incubadora de Empresas; Argentina
description After showing in a previous publication a clear superiority to the classic Peng-Robinson EoS for the description of high pressure phase behavior in the more asymmetric alkane-alkane binary mixtures, in this work the RKPR EoS is turned into a predictive model by developing correlations of interaction parameters for all possible pairs or normal alkanes, associated also to a new parameterization of pure compounds. The proposed correlations are based on van der Waals quadratic mixing rules. Repulsive interaction lij parameters are implemented in all cases, while attractive kij interactions were necessary only for the methane-series and the more asymmetric systems of propane, in particular with carbon numbers higher than 24. The analysis of the results, in comparison to an important diversity of data available for several dozens of systems, demonstrates a very good predictive power for the new correlations, which could be useful in modeling the phase behavior of different hydrocarbon fluids.
publishDate 2015
dc.date.none.fl_str_mv 2015-10-15
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/11336/43792
Cismondi Duarte, Martín; Cruz Doblas, J.; Gomez, M. J.; Montoya, Gerardo Federico; Modelling the phase behavior of alkane mixtures in wide ranges of conditions: New parameterization and predictive correlations of binary interactions for the RKPR EOS; Elsevier Science; Fluid Phase Equilibria; 403; 15-10-2015; 49-59
0378-3812
CONICET Digital
CONICET
url http://hdl.handle.net/11336/43792
identifier_str_mv Cismondi Duarte, Martín; Cruz Doblas, J.; Gomez, M. J.; Montoya, Gerardo Federico; Modelling the phase behavior of alkane mixtures in wide ranges of conditions: New parameterization and predictive correlations of binary interactions for the RKPR EOS; Elsevier Science; Fluid Phase Equilibria; 403; 15-10-2015; 49-59
0378-3812
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/j.fluid.2015.06.005
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0378381215003246?via%3Dihub
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 Science
publisher.none.fl_str_mv Elsevier Science
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
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score 12.982451

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