Quantization-based new integration methods for stiff ordinary differential equations

Autores
Migoni, Gustavo Andres; Kofman, Ernesto Javier; Cellier, François
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this paper we introduce new classes of numerical ordinary differential equation (ODE) solvers that base their internal discretization method on state quantization instead of time slicing. These solvers have been coined quantized state system (QSS) simulators. The primary result of the research described in this article is a first-order accurate QSS-based stiff system solver, called the backward QSS (BQSS). The numerical properties of this new algorithm are discussed, and it is shown that this algorithm exhibits properties that make it a potentially attractive alternative to the classical numerical ODE solvers. Some simulation examples illustrate the advantages of this method. As a collateral result, a first-order accurate QSS-based solver designed for solving marginally stable systems is briefly outlined as well. This new method, called the centered QSS (CQSS), is successfully applied to a challenging benchmark problem describing a high-order system that is simultaneously stiff and marginally stable. However, the primary emphasis of this article is on the BQSS method, that is, on a stiff system solver based on state quantization.
Fil: Migoni, Gustavo Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Cellier, François. Eidgenössische Technische Hochschule Zürich; Suiza
Materia
DISCRETE EVENT SYSTEM
QUANTIZED STATE SYSTEMS
STIFF SYSTEMS
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:11336/186683
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Quantization-based new integration methods for stiff ordinary differential equationsMigoni, Gustavo AndresKofman, Ernesto JavierCellier, FrançoisDISCRETE EVENT SYSTEMQUANTIZED STATE SYSTEMSSTIFF SYSTEMShttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2In this paper we introduce new classes of numerical ordinary differential equation (ODE) solvers that base their internal discretization method on state quantization instead of time slicing. These solvers have been coined quantized state system (QSS) simulators. The primary result of the research described in this article is a first-order accurate QSS-based stiff system solver, called the backward QSS (BQSS). The numerical properties of this new algorithm are discussed, and it is shown that this algorithm exhibits properties that make it a potentially attractive alternative to the classical numerical ODE solvers. Some simulation examples illustrate the advantages of this method. As a collateral result, a first-order accurate QSS-based solver designed for solving marginally stable systems is briefly outlined as well. This new method, called the centered QSS (CQSS), is successfully applied to a challenging benchmark problem describing a high-order system that is simultaneously stiff and marginally stable. However, the primary emphasis of this article is on the BQSS method, that is, on a stiff system solver based on state quantization.Fil: Migoni, Gustavo Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Cellier, François. Eidgenössische Technische Hochschule Zürich; SuizaSage Publications Ltd2012-04info: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/11336/186683Migoni, Gustavo Andres; Kofman, Ernesto Javier; Cellier, François; Quantization-based new integration methods for stiff ordinary differential equations; Sage Publications Ltd; Simulation; 88; 4; 4-2012; 387-4070037-5497CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://sim.sagepub.com/content/early/2011/06/07/0037549711403645.full.pdf+htmlinfo:eu-repo/semantics/altIdentifier/doi/10.1177/0037549711403645info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:06:18Zoai:ri.conicet.gov.ar:11336/186683instacron: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 10:06:18.886CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Quantization-based new integration methods for stiff ordinary differential equations
title Quantization-based new integration methods for stiff ordinary differential equations
spellingShingle Quantization-based new integration methods for stiff ordinary differential equations
Migoni, Gustavo Andres
DISCRETE EVENT SYSTEM
QUANTIZED STATE SYSTEMS
STIFF SYSTEMS
title_short Quantization-based new integration methods for stiff ordinary differential equations
title_full Quantization-based new integration methods for stiff ordinary differential equations
title_fullStr Quantization-based new integration methods for stiff ordinary differential equations
title_full_unstemmed Quantization-based new integration methods for stiff ordinary differential equations
title_sort Quantization-based new integration methods for stiff ordinary differential equations
dc.creator.none.fl_str_mv Migoni, Gustavo Andres
Kofman, Ernesto Javier
Cellier, François
author Migoni, Gustavo Andres
author_facet Migoni, Gustavo Andres
Kofman, Ernesto Javier
Cellier, François
author_role author
author2 Kofman, Ernesto Javier
Cellier, François
author2_role author
author
dc.subject.none.fl_str_mv DISCRETE EVENT SYSTEM
QUANTIZED STATE SYSTEMS
STIFF SYSTEMS
topic DISCRETE EVENT SYSTEM
QUANTIZED STATE SYSTEMS
STIFF SYSTEMS
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv In this paper we introduce new classes of numerical ordinary differential equation (ODE) solvers that base their internal discretization method on state quantization instead of time slicing. These solvers have been coined quantized state system (QSS) simulators. The primary result of the research described in this article is a first-order accurate QSS-based stiff system solver, called the backward QSS (BQSS). The numerical properties of this new algorithm are discussed, and it is shown that this algorithm exhibits properties that make it a potentially attractive alternative to the classical numerical ODE solvers. Some simulation examples illustrate the advantages of this method. As a collateral result, a first-order accurate QSS-based solver designed for solving marginally stable systems is briefly outlined as well. This new method, called the centered QSS (CQSS), is successfully applied to a challenging benchmark problem describing a high-order system that is simultaneously stiff and marginally stable. However, the primary emphasis of this article is on the BQSS method, that is, on a stiff system solver based on state quantization.
Fil: Migoni, Gustavo Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Cellier, François. Eidgenössische Technische Hochschule Zürich; Suiza
description In this paper we introduce new classes of numerical ordinary differential equation (ODE) solvers that base their internal discretization method on state quantization instead of time slicing. These solvers have been coined quantized state system (QSS) simulators. The primary result of the research described in this article is a first-order accurate QSS-based stiff system solver, called the backward QSS (BQSS). The numerical properties of this new algorithm are discussed, and it is shown that this algorithm exhibits properties that make it a potentially attractive alternative to the classical numerical ODE solvers. Some simulation examples illustrate the advantages of this method. As a collateral result, a first-order accurate QSS-based solver designed for solving marginally stable systems is briefly outlined as well. This new method, called the centered QSS (CQSS), is successfully applied to a challenging benchmark problem describing a high-order system that is simultaneously stiff and marginally stable. However, the primary emphasis of this article is on the BQSS method, that is, on a stiff system solver based on state quantization.
publishDate 2012
dc.date.none.fl_str_mv 2012-04
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/11336/186683
Migoni, Gustavo Andres; Kofman, Ernesto Javier; Cellier, François; Quantization-based new integration methods for stiff ordinary differential equations; Sage Publications Ltd; Simulation; 88; 4; 4-2012; 387-407
0037-5497
CONICET Digital
CONICET
url http://hdl.handle.net/11336/186683
identifier_str_mv Migoni, Gustavo Andres; Kofman, Ernesto Javier; Cellier, François; Quantization-based new integration methods for stiff ordinary differential equations; Sage Publications Ltd; Simulation; 88; 4; 4-2012; 387-407
0037-5497
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://sim.sagepub.com/content/early/2011/06/07/0037549711403645.full.pdf+html
info:eu-repo/semantics/altIdentifier/doi/10.1177/0037549711403645
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
application/pdf
dc.publisher.none.fl_str_mv Sage Publications Ltd
publisher.none.fl_str_mv Sage Publications 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 13.13397

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