Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems
The flow-driven spectral chaos (FSC) is a recently developed method for tracking and quantifying uncertainties in the long-time response of stochastic dynamical systems using the spectral approach. The method uses a novel concept called enriched stochastic flow maps as a means to construct an evolvi...
- Autores:
-
Esquivel, Hugo
Prakash, Arun
Lin, Guang
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2022
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/9463
- Acceso en línea:
- https://hdl.handle.net/11323/9463
https://doi.org/10.1016/j.jcp.2022.111425
https://repositorio.cuc.edu.co/
- Palabra clave:
- Stochastic discontinuities
Stochastic dynamical systems
Uncertainty quantification
Long-time integration
Stochastic flow map
Multi-element flow-driven spectral chaos (ME-FSC)
- Rights
- embargoedAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
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dc.title.eng.fl_str_mv |
Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems |
title |
Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems |
spellingShingle |
Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems Stochastic discontinuities Stochastic dynamical systems Uncertainty quantification Long-time integration Stochastic flow map Multi-element flow-driven spectral chaos (ME-FSC) |
title_short |
Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems |
title_full |
Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems |
title_fullStr |
Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems |
title_full_unstemmed |
Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems |
title_sort |
Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems |
dc.creator.fl_str_mv |
Esquivel, Hugo Prakash, Arun Lin, Guang |
dc.contributor.author.spa.fl_str_mv |
Esquivel, Hugo Prakash, Arun Lin, Guang |
dc.subject.proposal.eng.fl_str_mv |
Stochastic discontinuities Stochastic dynamical systems Uncertainty quantification Long-time integration Stochastic flow map Multi-element flow-driven spectral chaos (ME-FSC) |
topic |
Stochastic discontinuities Stochastic dynamical systems Uncertainty quantification Long-time integration Stochastic flow map Multi-element flow-driven spectral chaos (ME-FSC) |
description |
The flow-driven spectral chaos (FSC) is a recently developed method for tracking and quantifying uncertainties in the long-time response of stochastic dynamical systems using the spectral approach. The method uses a novel concept called enriched stochastic flow maps as a means to construct an evolving finite-dimensional random function space that is both accurate and computationally efficient in time. In this paper, we present a multi-element version of the FSC method (the ME-FSC method for short) to tackle (mainly) those dynamical systems that are inherently discontinuous over the probability space. In ME-FSC, the random domain is partitioned into several elements, and then the problem is solved separately on each random element using the FSC method. Subsequently, results are aggregated to compute the probability moments of interest using the law of total probability. To demonstrate the effectiveness of the ME-FSC method in dealing with discontinuities and long-time integration of stochastic dynamical systems, four representative numerical examples are presented in this paper, including the Van-der-Pol oscillator problem and the Kraichnan-Orszag three-mode problem. Results show that the ME-FSC method is capable of solving problems that have strong nonlinear dependencies over the probability space, both reliably and at low computational cost. |
publishDate |
2022 |
dc.date.accessioned.none.fl_str_mv |
2022-08-22T20:42:17Z |
dc.date.available.none.fl_str_mv |
2022-08-22T20:42:17Z 2024 |
dc.date.issued.none.fl_str_mv |
2022 |
dc.type.spa.fl_str_mv |
Artículo de revista |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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http://purl.org/coar/resource_type/c_6501 |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/ART |
format |
http://purl.org/coar/resource_type/c_6501 |
dc.identifier.citation.spa.fl_str_mv |
Hugo Esquivel, Arun Prakash, Guang Lin, Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems, Journal of Computational Physics, Volume 467, 2022, 111425, ISSN 0021-9991, https://doi.org/10.1016/j.jcp.2022.111425. |
dc.identifier.issn.spa.fl_str_mv |
0021-9991 |
dc.identifier.uri.spa.fl_str_mv |
https://hdl.handle.net/11323/9463 |
dc.identifier.url.spa.fl_str_mv |
https://doi.org/10.1016/j.jcp.2022.111425 |
dc.identifier.doi.spa.fl_str_mv |
10.1016/j.jcp.2022.111425 |
dc.identifier.instname.spa.fl_str_mv |
Corporación Universidad de la Costa |
dc.identifier.reponame.spa.fl_str_mv |
REDICUC - Repositorio CUC |
dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.cuc.edu.co/ |
identifier_str_mv |
Hugo Esquivel, Arun Prakash, Guang Lin, Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems, Journal of Computational Physics, Volume 467, 2022, 111425, ISSN 0021-9991, https://doi.org/10.1016/j.jcp.2022.111425. 0021-9991 10.1016/j.jcp.2022.111425 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
url |
https://hdl.handle.net/11323/9463 https://doi.org/10.1016/j.jcp.2022.111425 https://repositorio.cuc.edu.co/ |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartofjournal.spa.fl_str_mv |
Journal of Computational Physics |
dc.relation.citationvolume.spa.fl_str_mv |
467 |
dc.rights.spa.fl_str_mv |
Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) © 2022 Elsevier B.V. |
dc.rights.uri.spa.fl_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
dc.rights.coar.spa.fl_str_mv |
http://purl.org/coar/access_right/c_f1cf |
rights_invalid_str_mv |
Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) © 2022 Elsevier B.V. https://creativecommons.org/licenses/by-nc-nd/4.0/ http://purl.org/coar/access_right/c_f1cf |
eu_rights_str_mv |
embargoedAccess |
dc.format.extent.spa.fl_str_mv |
1 página |
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dc.publisher.spa.fl_str_mv |
Academic Press Inc. |
dc.publisher.place.spa.fl_str_mv |
United States |
institution |
Corporación Universidad de la Costa |
dc.source.url.spa.fl_str_mv |
https://www.sciencedirect.com/science/article/pii/S0021999122004879?via%3Dihub |
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Esquivel, HugoPrakash, ArunLin, Guang2022-08-22T20:42:17Z20242022-08-22T20:42:17Z2022Hugo Esquivel, Arun Prakash, Guang Lin, Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems, Journal of Computational Physics, Volume 467, 2022, 111425, ISSN 0021-9991, https://doi.org/10.1016/j.jcp.2022.111425.0021-9991https://hdl.handle.net/11323/9463https://doi.org/10.1016/j.jcp.2022.11142510.1016/j.jcp.2022.111425Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/The flow-driven spectral chaos (FSC) is a recently developed method for tracking and quantifying uncertainties in the long-time response of stochastic dynamical systems using the spectral approach. The method uses a novel concept called enriched stochastic flow maps as a means to construct an evolving finite-dimensional random function space that is both accurate and computationally efficient in time. In this paper, we present a multi-element version of the FSC method (the ME-FSC method for short) to tackle (mainly) those dynamical systems that are inherently discontinuous over the probability space. In ME-FSC, the random domain is partitioned into several elements, and then the problem is solved separately on each random element using the FSC method. Subsequently, results are aggregated to compute the probability moments of interest using the law of total probability. To demonstrate the effectiveness of the ME-FSC method in dealing with discontinuities and long-time integration of stochastic dynamical systems, four representative numerical examples are presented in this paper, including the Van-der-Pol oscillator problem and the Kraichnan-Orszag three-mode problem. Results show that the ME-FSC method is capable of solving problems that have strong nonlinear dependencies over the probability space, both reliably and at low computational cost.1 páginaapplication/pdfengAcademic Press Inc.United StatesAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)© 2022 Elsevier B.V.https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/embargoedAccesshttp://purl.org/coar/access_right/c_f1cfMulti-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systemsArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85https://www.sciencedirect.com/science/article/pii/S0021999122004879?via%3DihubJournal of Computational Physics467Stochastic discontinuitiesStochastic dynamical systemsUncertainty quantificationLong-time 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