A Decomposition Method for Synthesizing Complex Column Configurations Using Tray-by-Tray GDP Models

Autores
Barttfeld, Mariana; Aguirre, Pio Antonio; Grossmann, Ignacio E.
Año de publicación
2004
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper describes an optimization procedure for the synthesis of complex distillation configurations. A superstructure based on the Reversible Distillation Sequence Model (RDSM) is proposed embedding all possible alternative designs using tray-by-tray models. Generalize disjunctive programming (GDP) is used to model the superstructure. Each column section of the superstructure is modeled using rigorous MESH equations. Due to the large size and complexity of the formulation, as well as the great difficulty in coverging the corresponding equations, a decomposition solution strategy is proposed where discrete decisions are decomposed into two hierarchical levels within an iterative procedure. In the first level, the column sections are selected yielding a candidate configuration. In the second level, the feed location and the number of trays of the selected sections are optimized. A preprocessing phase including thermodynamic information is considered to provide a good starting point to the algorithm in order to improve the convergence and robustness of the method. Examples are presented for zeotropic and azeotropic multicomponent mixtures to illustrate the performance of the proposed method. Non-trivial configurations are obtained involving modest solution times.
Fil: Barttfeld, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Aguirre, Pio Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Grossmann, Ignacio E.. University of Carnegie Mellon; Estados Unidos
Materia
COMPLEX DISTILLATION COLUMNS
DISJUNCTIVE PROGRAMMING
INITIALIZATION
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:11336/186295
Acceder
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network_name_str CONICET Digital (CONICET)
spelling A Decomposition Method for Synthesizing Complex Column Configurations Using Tray-by-Tray GDP ModelsBarttfeld, MarianaAguirre, Pio AntonioGrossmann, Ignacio E.COMPLEX DISTILLATION COLUMNSDISJUNCTIVE PROGRAMMINGINITIALIZATIONhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2This paper describes an optimization procedure for the synthesis of complex distillation configurations. A superstructure based on the Reversible Distillation Sequence Model (RDSM) is proposed embedding all possible alternative designs using tray-by-tray models. Generalize disjunctive programming (GDP) is used to model the superstructure. Each column section of the superstructure is modeled using rigorous MESH equations. Due to the large size and complexity of the formulation, as well as the great difficulty in coverging the corresponding equations, a decomposition solution strategy is proposed where discrete decisions are decomposed into two hierarchical levels within an iterative procedure. In the first level, the column sections are selected yielding a candidate configuration. In the second level, the feed location and the number of trays of the selected sections are optimized. A preprocessing phase including thermodynamic information is considered to provide a good starting point to the algorithm in order to improve the convergence and robustness of the method. Examples are presented for zeotropic and azeotropic multicomponent mixtures to illustrate the performance of the proposed method. Non-trivial configurations are obtained involving modest solution times.Fil: Barttfeld, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Aguirre, Pio Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Grossmann, Ignacio E.. University of Carnegie Mellon; Estados UnidosPergamon-Elsevier Science Ltd2004-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/186295Barttfeld, Mariana; Aguirre, Pio Antonio; Grossmann, Ignacio E.; A Decomposition Method for Synthesizing Complex Column Configurations Using Tray-by-Tray GDP Models; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 28; 11; 10-2004; 2165-21880098-1354CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0098135404000699info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2004.03.006info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:57:07Zoai:ri.conicet.gov.ar:11336/186295instacron: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:34982025-09-29 09:57:07.519CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A Decomposition Method for Synthesizing Complex Column Configurations Using Tray-by-Tray GDP Models
title A Decomposition Method for Synthesizing Complex Column Configurations Using Tray-by-Tray GDP Models
spellingShingle A Decomposition Method for Synthesizing Complex Column Configurations Using Tray-by-Tray GDP Models
Barttfeld, Mariana
COMPLEX DISTILLATION COLUMNS
DISJUNCTIVE PROGRAMMING
INITIALIZATION
title_short A Decomposition Method for Synthesizing Complex Column Configurations Using Tray-by-Tray GDP Models
title_full A Decomposition Method for Synthesizing Complex Column Configurations Using Tray-by-Tray GDP Models
title_fullStr A Decomposition Method for Synthesizing Complex Column Configurations Using Tray-by-Tray GDP Models
title_full_unstemmed A Decomposition Method for Synthesizing Complex Column Configurations Using Tray-by-Tray GDP Models
title_sort A Decomposition Method for Synthesizing Complex Column Configurations Using Tray-by-Tray GDP Models
dc.creator.none.fl_str_mv Barttfeld, Mariana
Aguirre, Pio Antonio
Grossmann, Ignacio E.
author Barttfeld, Mariana
author_facet Barttfeld, Mariana
Aguirre, Pio Antonio
Grossmann, Ignacio E.
author_role author
author2 Aguirre, Pio Antonio
Grossmann, Ignacio E.
author2_role author
author
dc.subject.none.fl_str_mv COMPLEX DISTILLATION COLUMNS
DISJUNCTIVE PROGRAMMING
INITIALIZATION
topic COMPLEX DISTILLATION COLUMNS
DISJUNCTIVE PROGRAMMING
INITIALIZATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This paper describes an optimization procedure for the synthesis of complex distillation configurations. A superstructure based on the Reversible Distillation Sequence Model (RDSM) is proposed embedding all possible alternative designs using tray-by-tray models. Generalize disjunctive programming (GDP) is used to model the superstructure. Each column section of the superstructure is modeled using rigorous MESH equations. Due to the large size and complexity of the formulation, as well as the great difficulty in coverging the corresponding equations, a decomposition solution strategy is proposed where discrete decisions are decomposed into two hierarchical levels within an iterative procedure. In the first level, the column sections are selected yielding a candidate configuration. In the second level, the feed location and the number of trays of the selected sections are optimized. A preprocessing phase including thermodynamic information is considered to provide a good starting point to the algorithm in order to improve the convergence and robustness of the method. Examples are presented for zeotropic and azeotropic multicomponent mixtures to illustrate the performance of the proposed method. Non-trivial configurations are obtained involving modest solution times.
Fil: Barttfeld, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Aguirre, Pio Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Grossmann, Ignacio E.. University of Carnegie Mellon; Estados Unidos
description This paper describes an optimization procedure for the synthesis of complex distillation configurations. A superstructure based on the Reversible Distillation Sequence Model (RDSM) is proposed embedding all possible alternative designs using tray-by-tray models. Generalize disjunctive programming (GDP) is used to model the superstructure. Each column section of the superstructure is modeled using rigorous MESH equations. Due to the large size and complexity of the formulation, as well as the great difficulty in coverging the corresponding equations, a decomposition solution strategy is proposed where discrete decisions are decomposed into two hierarchical levels within an iterative procedure. In the first level, the column sections are selected yielding a candidate configuration. In the second level, the feed location and the number of trays of the selected sections are optimized. A preprocessing phase including thermodynamic information is considered to provide a good starting point to the algorithm in order to improve the convergence and robustness of the method. Examples are presented for zeotropic and azeotropic multicomponent mixtures to illustrate the performance of the proposed method. Non-trivial configurations are obtained involving modest solution times.
publishDate 2004
dc.date.none.fl_str_mv 2004-10
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/11336/186295
Barttfeld, Mariana; Aguirre, Pio Antonio; Grossmann, Ignacio E.; A Decomposition Method for Synthesizing Complex Column Configurations Using Tray-by-Tray GDP Models; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 28; 11; 10-2004; 2165-2188
0098-1354
CONICET Digital
CONICET
url http://hdl.handle.net/11336/186295
identifier_str_mv Barttfeld, Mariana; Aguirre, Pio Antonio; Grossmann, Ignacio E.; A Decomposition Method for Synthesizing Complex Column Configurations Using Tray-by-Tray GDP Models; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 28; 11; 10-2004; 2165-2188
0098-1354
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0098135404000699
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2004.03.006
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 Pergamon-Elsevier Science Ltd
publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
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 13.070432

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