Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence

Particle-laden turbulent flows subject to radiative heating are relevant in many applications, for example concentrated solar power receivers. Efficient and accurate simulations provide valuable insights and enable optimization of such systems. However, as there are many uncertainties inherent in su...

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Autores: Fairbanks, Hillary R., Jofre Cruanyes, Lluís|||0000-0003-2437-259X
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/187290
Acceso en línea:https://hdl.handle.net/2117/187290
https://dx.doi.org/10.1016/j.jcp.2019.108996
Access Level:acceso abierto
Palabra clave:Turbulence
Bi-fidelity approximation
Irradiated particle-laden turbulence
Low-rank approximation
Non-intrusive
Predictive computational science
Uncertainty quantification
Turbulència
Àrees temàtiques de la UPC::Física
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spelling Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulenceFairbanks, Hillary R.Jofre Cruanyes, Lluís|||0000-0003-2437-259XTurbulenceBi-fidelity approximationIrradiated particle-laden turbulenceLow-rank approximationNon-intrusivePredictive computational scienceUncertainty quantificationTurbulènciaÀrees temàtiques de la UPC::FísicaParticle-laden turbulent flows subject to radiative heating are relevant in many applications, for example concentrated solar power receivers. Efficient and accurate simulations provide valuable insights and enable optimization of such systems. However, as there are many uncertainties inherent in such flows, uncertainty quantification is fundamental to improve the predictive capabilities of the numerical simulations. For large-scale, multi-physics problems exhibiting high-dimensional uncertainty, characterizing the stochastic solution presents a significant computational challenge as most strategies require a large number of high-fidelity solves. This requirement might result in an infeasible number of simulations when a typical converged high-fidelity simulation requires intensive computational resources. To reduce the cost of quantifying high-dimensional uncertainties, we investigate the application of a non-intrusive, bi-fidelity approximation to estimate statistics of quantities of interest associated with an irradiated particle-laden turbulent flow. This method exploits the low-rank structure of the solution to accelerate the stochastic sampling and approximation processes by means of cheaper-to-run, lower fidelity representations. The application of this bi-fidelity approximation results in accurate estimates of the quantities of interest statistics, while requiring a small number of high-fidelity model evaluations.Peer Reviewed20202020-02-0120202020-05-12journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/187290https://dx.doi.org/10.1016/j.jcp.2019.108996reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1872902026-05-27T15:37:01Z
dc.title.none.fl_str_mv Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence
title Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence
spellingShingle Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence
Fairbanks, Hillary R.
Turbulence
Bi-fidelity approximation
Irradiated particle-laden turbulence
Low-rank approximation
Non-intrusive
Predictive computational science
Uncertainty quantification
Turbulència
Àrees temàtiques de la UPC::Física
title_short Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence
title_full Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence
title_fullStr Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence
title_full_unstemmed Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence
title_sort Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence
dc.creator.none.fl_str_mv Fairbanks, Hillary R.
Jofre Cruanyes, Lluís|||0000-0003-2437-259X
author Fairbanks, Hillary R.
author_facet Fairbanks, Hillary R.
Jofre Cruanyes, Lluís|||0000-0003-2437-259X
author_role author
author2 Jofre Cruanyes, Lluís|||0000-0003-2437-259X
author2_role author
dc.subject.none.fl_str_mv Turbulence
Bi-fidelity approximation
Irradiated particle-laden turbulence
Low-rank approximation
Non-intrusive
Predictive computational science
Uncertainty quantification
Turbulència
Àrees temàtiques de la UPC::Física
topic Turbulence
Bi-fidelity approximation
Irradiated particle-laden turbulence
Low-rank approximation
Non-intrusive
Predictive computational science
Uncertainty quantification
Turbulència
Àrees temàtiques de la UPC::Física
description Particle-laden turbulent flows subject to radiative heating are relevant in many applications, for example concentrated solar power receivers. Efficient and accurate simulations provide valuable insights and enable optimization of such systems. However, as there are many uncertainties inherent in such flows, uncertainty quantification is fundamental to improve the predictive capabilities of the numerical simulations. For large-scale, multi-physics problems exhibiting high-dimensional uncertainty, characterizing the stochastic solution presents a significant computational challenge as most strategies require a large number of high-fidelity solves. This requirement might result in an infeasible number of simulations when a typical converged high-fidelity simulation requires intensive computational resources. To reduce the cost of quantifying high-dimensional uncertainties, we investigate the application of a non-intrusive, bi-fidelity approximation to estimate statistics of quantities of interest associated with an irradiated particle-laden turbulent flow. This method exploits the low-rank structure of the solution to accelerate the stochastic sampling and approximation processes by means of cheaper-to-run, lower fidelity representations. The application of this bi-fidelity approximation results in accurate estimates of the quantities of interest statistics, while requiring a small number of high-fidelity model evaluations.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-02-01
2020
2020-05-12
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/187290
https://dx.doi.org/10.1016/j.jcp.2019.108996
url https://hdl.handle.net/2117/187290
https://dx.doi.org/10.1016/j.jcp.2019.108996
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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