Linearly implicit quantization-based integration methods for stiff ordinary differential equations

Autores
Migoni, Gustavo Andres; Bortolotto López, Mario Luciano; Kofmam, Ernesto; Cellier, François
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this paper, new integration methods for stiff ordinary differential equations (ODEs) are developed. Following the idea of quantization-based integration (QBI), i.e., replacing the time discretization by state quantization, the proposed algorithms generalize the idea of linearly implicit algorithms. Also, the implementation of the new algorithms in a DEVS simulation tool is discussed. The efficiency of these new methods is verified by comparing their performance in the simulation of two benchmark problems with that of other numerical stiff ODE solvers. In particular, the advantages of these new algorithms for the simulation of electronic circuits are demonstrated.
Fil: Migoni, Gustavo Andres. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura. Departamento de Control; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Fil: Bortolotto López, Mario Luciano. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura. Departamento de Control; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Fil: Kofmam, Ernesto. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura. Departamento de Control; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Fil: Cellier, François. Swiss Federal Institute of Technology Zurich; Suiza
Materia
Ordinary Differential Equations
Stiff Systems
State Quantization
Quantized State Systems
Powerdevs
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/3195
Acceder
id CONICETDig_433285145c05f9f5b0ac8b453ed558eb
oai_identifier_str oai:ri.conicet.gov.ar:11336/3195
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Linearly implicit quantization-based integration methods for stiff ordinary differential equationsMigoni, Gustavo AndresBortolotto López, Mario LucianoKofmam, ErnestoCellier, FrançoisOrdinary Differential EquationsStiff SystemsState QuantizationQuantized State SystemsPowerdevshttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1In this paper, new integration methods for stiff ordinary differential equations (ODEs) are developed. Following the idea of quantization-based integration (QBI), i.e., replacing the time discretization by state quantization, the proposed algorithms generalize the idea of linearly implicit algorithms. Also, the implementation of the new algorithms in a DEVS simulation tool is discussed. The efficiency of these new methods is verified by comparing their performance in the simulation of two benchmark problems with that of other numerical stiff ODE solvers. In particular, the advantages of these new algorithms for the simulation of electronic circuits are demonstrated.Fil: Migoni, Gustavo Andres. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura. Departamento de Control; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; ArgentinaFil: Bortolotto López, Mario Luciano. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura. Departamento de Control; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; ArgentinaFil: Kofmam, Ernesto. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura. Departamento de Control; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; ArgentinaFil: Cellier, François. Swiss Federal Institute of Technology Zurich; SuizaElsevier2013-05-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/3195Migoni, Gustavo Andres; Bortolotto López, Mario Luciano; Kofmam, Ernesto; Cellier, François; Linearly implicit quantization-based integration methods for stiff ordinary differential equations; Elsevier; Simulation Modelling Practice and Theory; 35; 3-5-2013; 118-1361569-190Xenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S1569190X13000403info:eu-repo/semantics/altIdentifier/doi/10.1016/j.simpat.2013.03.004info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:01:36Zoai:ri.conicet.gov.ar:11336/3195instacron: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:34982025-09-03 10:01:37.214CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Linearly implicit quantization-based integration methods for stiff ordinary differential equations
title Linearly implicit quantization-based integration methods for stiff ordinary differential equations
spellingShingle Linearly implicit quantization-based integration methods for stiff ordinary differential equations
Migoni, Gustavo Andres
Ordinary Differential Equations
Stiff Systems
State Quantization
Quantized State Systems
Powerdevs
title_short Linearly implicit quantization-based integration methods for stiff ordinary differential equations
title_full Linearly implicit quantization-based integration methods for stiff ordinary differential equations
title_fullStr Linearly implicit quantization-based integration methods for stiff ordinary differential equations
title_full_unstemmed Linearly implicit quantization-based integration methods for stiff ordinary differential equations
title_sort Linearly implicit quantization-based integration methods for stiff ordinary differential equations
dc.creator.none.fl_str_mv Migoni, Gustavo Andres
Bortolotto López, Mario Luciano
Kofmam, Ernesto
Cellier, François
author Migoni, Gustavo Andres
author_facet Migoni, Gustavo Andres
Bortolotto López, Mario Luciano
Kofmam, Ernesto
Cellier, François
author_role author
author2 Bortolotto López, Mario Luciano
Kofmam, Ernesto
Cellier, François
author2_role author
author
author
dc.subject.none.fl_str_mv Ordinary Differential Equations
Stiff Systems
State Quantization
Quantized State Systems
Powerdevs
topic Ordinary Differential Equations
Stiff Systems
State Quantization
Quantized State Systems
Powerdevs
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In this paper, new integration methods for stiff ordinary differential equations (ODEs) are developed. Following the idea of quantization-based integration (QBI), i.e., replacing the time discretization by state quantization, the proposed algorithms generalize the idea of linearly implicit algorithms. Also, the implementation of the new algorithms in a DEVS simulation tool is discussed. The efficiency of these new methods is verified by comparing their performance in the simulation of two benchmark problems with that of other numerical stiff ODE solvers. In particular, the advantages of these new algorithms for the simulation of electronic circuits are demonstrated.
Fil: Migoni, Gustavo Andres. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura. Departamento de Control; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Fil: Bortolotto López, Mario Luciano. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura. Departamento de Control; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Fil: Kofmam, Ernesto. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura. Departamento de Control; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Fil: Cellier, François. Swiss Federal Institute of Technology Zurich; Suiza
description In this paper, new integration methods for stiff ordinary differential equations (ODEs) are developed. Following the idea of quantization-based integration (QBI), i.e., replacing the time discretization by state quantization, the proposed algorithms generalize the idea of linearly implicit algorithms. Also, the implementation of the new algorithms in a DEVS simulation tool is discussed. The efficiency of these new methods is verified by comparing their performance in the simulation of two benchmark problems with that of other numerical stiff ODE solvers. In particular, the advantages of these new algorithms for the simulation of electronic circuits are demonstrated.
publishDate 2013
dc.date.none.fl_str_mv 2013-05-03
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/11336/3195
Migoni, Gustavo Andres; Bortolotto López, Mario Luciano; Kofmam, Ernesto; Cellier, François; Linearly implicit quantization-based integration methods for stiff ordinary differential equations; Elsevier; Simulation Modelling Practice and Theory; 35; 3-5-2013; 118-136
1569-190X
url http://hdl.handle.net/11336/3195
identifier_str_mv Migoni, Gustavo Andres; Bortolotto López, Mario Luciano; Kofmam, Ernesto; Cellier, François; Linearly implicit quantization-based integration methods for stiff ordinary differential equations; Elsevier; Simulation Modelling Practice and Theory; 35; 3-5-2013; 118-136
1569-190X
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S1569190X13000403
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.simpat.2013.03.004
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
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_ 1842269706954735616
score 13.13397

Publicaciones similares