Gradient subgrid-scale model for relativistic MHD large-eddy simulations

Autores
Carrasco, Federico León; Viganò, Daniele; Palenzuela, Carlos
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Magnetohydrodynamics (MHD) turbulence is likely to play an important role in several astrophysical scenarios, where the magnetic Reynolds is very large. Numerically, these cases can be studied efficiently by means of large-eddy simulations, in which the computational resources are used to evolve the system only up to a finite grid size. The resolution is not fine enough to capture all the relevant small-scale physics at play, which is instead effectively modeled by a set of additional terms in the evolution equations, dubbed as subgrid-scale model. Here we extend such approach, commonly used in nonrelativistic/nonmagnetic/incompressible fluid dynamics, to any general set of equation written in conservative form. We apply the so-called gradient model, giving recipes for these general balance-law systems, including the relevant case in which a nontrivial inversion of conserved to primitive fields is needed. In particular, we focus on the relativistic compressible ideal MHD scenario, by providing for the first time and for any equation of state, all the additional nontrivial subgrid-scale terms. As an application, we consider box simulations of the relativistic Kelvin-Helmholtz instability, which is also the first mechanism responsible for the magnetic field amplification in binary neutron star mergers and cannot be captured by the finest grid and longest simulations available (currently and in the near future). We numerically assess the performance of our model, by comparing it to the residuals coming from the filtering of high-resolution simulations. We find that the model can fit very well the residuals coming from filtering simulations with a resolution a few times higher. The application shown here explicitly considers the Minkovski metric, but it can be directly extended to general relativity, thus settling the basis to implement for the first time the gradient subgrid model in a general relativistic magnetohydrodynamics (GRMHD) binary merger large-eddy simulations. Our results suggest that this approach will be potentially able to unveil much better the small-scale dynamics achievable of full GRMHD simulations, or equivalently, to obtain the same results but saving a considerable amount of computational time.
Fil: Carrasco, Federico León. Universitat de les Illes Balears and Institut d’Estudis Espacials de Catalunya; Departament de Física; Palma de Mallorca; España. Max Planck Institute for Gravitational Physics; Alemania. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina
Fil: Viganò, Daniele. Universitat de les Illes Balears and Institut d’Estudis Espacials de Catalunya; Departament de Física; Palma de Mallorca; España. Universitat de les Illes Balears; Institut d’Aplicacions Computacionals de Codi Comunitari (IAC3); España
Fil: Palenzuela, Carlos. Universitat de les Illes Balears and Institut d’Estudis Espacials de Catalunya; Departament de Física; Palma de Mallorca; España. Universitat de les Illes Balears; Institut d’Aplicacions Computacionals de Codi Comunitari (IAC3); España
Materia
MAGNETOHYDRODYNAMICS
TURBULENCE
SUB-GRID-SCALE MODEL
LARGE-EDDY SIMULATIONS
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:11336/146064

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network_name_str CONICET Digital (CONICET)
spelling Gradient subgrid-scale model for relativistic MHD large-eddy simulationsCarrasco, Federico LeónViganò, DanielePalenzuela, CarlosMAGNETOHYDRODYNAMICSTURBULENCESUB-GRID-SCALE MODELLARGE-EDDY SIMULATIONShttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1Magnetohydrodynamics (MHD) turbulence is likely to play an important role in several astrophysical scenarios, where the magnetic Reynolds is very large. Numerically, these cases can be studied efficiently by means of large-eddy simulations, in which the computational resources are used to evolve the system only up to a finite grid size. The resolution is not fine enough to capture all the relevant small-scale physics at play, which is instead effectively modeled by a set of additional terms in the evolution equations, dubbed as subgrid-scale model. Here we extend such approach, commonly used in nonrelativistic/nonmagnetic/incompressible fluid dynamics, to any general set of equation written in conservative form. We apply the so-called gradient model, giving recipes for these general balance-law systems, including the relevant case in which a nontrivial inversion of conserved to primitive fields is needed. In particular, we focus on the relativistic compressible ideal MHD scenario, by providing for the first time and for any equation of state, all the additional nontrivial subgrid-scale terms. As an application, we consider box simulations of the relativistic Kelvin-Helmholtz instability, which is also the first mechanism responsible for the magnetic field amplification in binary neutron star mergers and cannot be captured by the finest grid and longest simulations available (currently and in the near future). We numerically assess the performance of our model, by comparing it to the residuals coming from the filtering of high-resolution simulations. We find that the model can fit very well the residuals coming from filtering simulations with a resolution a few times higher. The application shown here explicitly considers the Minkovski metric, but it can be directly extended to general relativity, thus settling the basis to implement for the first time the gradient subgrid model in a general relativistic magnetohydrodynamics (GRMHD) binary merger large-eddy simulations. Our results suggest that this approach will be potentially able to unveil much better the small-scale dynamics achievable of full GRMHD simulations, or equivalently, to obtain the same results but saving a considerable amount of computational time.Fil: Carrasco, Federico León. Universitat de les Illes Balears and Institut d’Estudis Espacials de Catalunya; Departament de Física; Palma de Mallorca; España. Max Planck Institute for Gravitational Physics; Alemania. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; ArgentinaFil: Viganò, Daniele. Universitat de les Illes Balears and Institut d’Estudis Espacials de Catalunya; Departament de Física; Palma de Mallorca; España. Universitat de les Illes Balears; Institut d’Aplicacions Computacionals de Codi Comunitari (IAC3); EspañaFil: Palenzuela, Carlos. Universitat de les Illes Balears and Institut d’Estudis Espacials de Catalunya; Departament de Física; Palma de Mallorca; España. Universitat de les Illes Balears; Institut d’Aplicacions Computacionals de Codi Comunitari (IAC3); EspañaAmerican Physical Society2020-03-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/146064Carrasco, Federico León; Viganò, Daniele; Palenzuela, Carlos; Gradient subgrid-scale model for relativistic MHD large-eddy simulations; American Physical Society; Physical Review D; 101; 6; 15-3-2020; 1-162470-00102470-0029CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1103/PhysRevD.101.063003info:eu-repo/semantics/altIdentifier/arxiv/https://arxiv.org/abs/1908.01419info:eu-repo/semantics/altIdentifier/url/https://journals.aps.org/prd/abstract/10.1103/PhysRevD.101.063003info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:51:14Zoai:ri.conicet.gov.ar:11336/146064instacron: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 09:51:15.262CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Gradient subgrid-scale model for relativistic MHD large-eddy simulations
title Gradient subgrid-scale model for relativistic MHD large-eddy simulations
spellingShingle Gradient subgrid-scale model for relativistic MHD large-eddy simulations
Carrasco, Federico León
MAGNETOHYDRODYNAMICS
TURBULENCE
SUB-GRID-SCALE MODEL
LARGE-EDDY SIMULATIONS
title_short Gradient subgrid-scale model for relativistic MHD large-eddy simulations
title_full Gradient subgrid-scale model for relativistic MHD large-eddy simulations
title_fullStr Gradient subgrid-scale model for relativistic MHD large-eddy simulations
title_full_unstemmed Gradient subgrid-scale model for relativistic MHD large-eddy simulations
title_sort Gradient subgrid-scale model for relativistic MHD large-eddy simulations
dc.creator.none.fl_str_mv Carrasco, Federico León
Viganò, Daniele
Palenzuela, Carlos
author Carrasco, Federico León
author_facet Carrasco, Federico León
Viganò, Daniele
Palenzuela, Carlos
author_role author
author2 Viganò, Daniele
Palenzuela, Carlos
author2_role author
author
dc.subject.none.fl_str_mv MAGNETOHYDRODYNAMICS
TURBULENCE
SUB-GRID-SCALE MODEL
LARGE-EDDY SIMULATIONS
topic MAGNETOHYDRODYNAMICS
TURBULENCE
SUB-GRID-SCALE MODEL
LARGE-EDDY SIMULATIONS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Magnetohydrodynamics (MHD) turbulence is likely to play an important role in several astrophysical scenarios, where the magnetic Reynolds is very large. Numerically, these cases can be studied efficiently by means of large-eddy simulations, in which the computational resources are used to evolve the system only up to a finite grid size. The resolution is not fine enough to capture all the relevant small-scale physics at play, which is instead effectively modeled by a set of additional terms in the evolution equations, dubbed as subgrid-scale model. Here we extend such approach, commonly used in nonrelativistic/nonmagnetic/incompressible fluid dynamics, to any general set of equation written in conservative form. We apply the so-called gradient model, giving recipes for these general balance-law systems, including the relevant case in which a nontrivial inversion of conserved to primitive fields is needed. In particular, we focus on the relativistic compressible ideal MHD scenario, by providing for the first time and for any equation of state, all the additional nontrivial subgrid-scale terms. As an application, we consider box simulations of the relativistic Kelvin-Helmholtz instability, which is also the first mechanism responsible for the magnetic field amplification in binary neutron star mergers and cannot be captured by the finest grid and longest simulations available (currently and in the near future). We numerically assess the performance of our model, by comparing it to the residuals coming from the filtering of high-resolution simulations. We find that the model can fit very well the residuals coming from filtering simulations with a resolution a few times higher. The application shown here explicitly considers the Minkovski metric, but it can be directly extended to general relativity, thus settling the basis to implement for the first time the gradient subgrid model in a general relativistic magnetohydrodynamics (GRMHD) binary merger large-eddy simulations. Our results suggest that this approach will be potentially able to unveil much better the small-scale dynamics achievable of full GRMHD simulations, or equivalently, to obtain the same results but saving a considerable amount of computational time.
Fil: Carrasco, Federico León. Universitat de les Illes Balears and Institut d’Estudis Espacials de Catalunya; Departament de Física; Palma de Mallorca; España. Max Planck Institute for Gravitational Physics; Alemania. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina
Fil: Viganò, Daniele. Universitat de les Illes Balears and Institut d’Estudis Espacials de Catalunya; Departament de Física; Palma de Mallorca; España. Universitat de les Illes Balears; Institut d’Aplicacions Computacionals de Codi Comunitari (IAC3); España
Fil: Palenzuela, Carlos. Universitat de les Illes Balears and Institut d’Estudis Espacials de Catalunya; Departament de Física; Palma de Mallorca; España. Universitat de les Illes Balears; Institut d’Aplicacions Computacionals de Codi Comunitari (IAC3); España
description Magnetohydrodynamics (MHD) turbulence is likely to play an important role in several astrophysical scenarios, where the magnetic Reynolds is very large. Numerically, these cases can be studied efficiently by means of large-eddy simulations, in which the computational resources are used to evolve the system only up to a finite grid size. The resolution is not fine enough to capture all the relevant small-scale physics at play, which is instead effectively modeled by a set of additional terms in the evolution equations, dubbed as subgrid-scale model. Here we extend such approach, commonly used in nonrelativistic/nonmagnetic/incompressible fluid dynamics, to any general set of equation written in conservative form. We apply the so-called gradient model, giving recipes for these general balance-law systems, including the relevant case in which a nontrivial inversion of conserved to primitive fields is needed. In particular, we focus on the relativistic compressible ideal MHD scenario, by providing for the first time and for any equation of state, all the additional nontrivial subgrid-scale terms. As an application, we consider box simulations of the relativistic Kelvin-Helmholtz instability, which is also the first mechanism responsible for the magnetic field amplification in binary neutron star mergers and cannot be captured by the finest grid and longest simulations available (currently and in the near future). We numerically assess the performance of our model, by comparing it to the residuals coming from the filtering of high-resolution simulations. We find that the model can fit very well the residuals coming from filtering simulations with a resolution a few times higher. The application shown here explicitly considers the Minkovski metric, but it can be directly extended to general relativity, thus settling the basis to implement for the first time the gradient subgrid model in a general relativistic magnetohydrodynamics (GRMHD) binary merger large-eddy simulations. Our results suggest that this approach will be potentially able to unveil much better the small-scale dynamics achievable of full GRMHD simulations, or equivalently, to obtain the same results but saving a considerable amount of computational time.
publishDate 2020
dc.date.none.fl_str_mv 2020-03-15
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/11336/146064
Carrasco, Federico León; Viganò, Daniele; Palenzuela, Carlos; Gradient subgrid-scale model for relativistic MHD large-eddy simulations; American Physical Society; Physical Review D; 101; 6; 15-3-2020; 1-16
2470-0010
2470-0029
CONICET Digital
CONICET
url http://hdl.handle.net/11336/146064
identifier_str_mv Carrasco, Federico León; Viganò, Daniele; Palenzuela, Carlos; Gradient subgrid-scale model for relativistic MHD large-eddy simulations; American Physical Society; Physical Review D; 101; 6; 15-3-2020; 1-16
2470-0010
2470-0029
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1103/PhysRevD.101.063003
info:eu-repo/semantics/altIdentifier/arxiv/https://arxiv.org/abs/1908.01419
info:eu-repo/semantics/altIdentifier/url/https://journals.aps.org/prd/abstract/10.1103/PhysRevD.101.063003
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 American Physical Society
publisher.none.fl_str_mv American Physical Society
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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