Two approaches to quantification of force networks in particulate systems

Autores
Basak, Rituparna; Carlevaro, Manuel; Kozlowski, Ryan; Cheng, Chao; Pugnaloni, Luis; Kramár, Miroslav; Zheng, Hu; Socolar, Joshua E. S.; Kondic, Lou
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The interactions between particles in particulate systems are organized in ‘force networks’, mesoscale features that bridge between the particle scale and the scale of the system as a whole. While such networks are known to be crucial in determining the system wide response, extracting their properties, particularly from experimental systems, is difficult due to the need to measure the interparticle forces. In this work, we show by analysis of the data extracted from simulations that such detailed information about interparticle forces may not be necessary, as long as the focus is on extracting the most dominant features of these networks. The main finding is that a reasonable understanding of the time evolution of force networks can be obtained from incomplete information such as total force on the particles. To compare the evolution of the networks based on the completely known particle interactions and the networks based on incomplete information (total force each grain) we use tools of algebraic topology. In particular we will compare simple measures defined on persistence diagrams that provide useful summaries of the force network features.
Fil: Basak, Rituparna. New Jersey Institute of Technology. Department of Mathematical Sciences. Newark, NJ; USA.
Fil: Carlevaro, Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos. La Plata; Argentina.
Fil: Carlevaro, Manuel. Universidad Tecnológica Nacional. Facultad Regional La Plata. Departamento de Ingeniería Mecánica; Argentina.
Fil: Kozlowski, Ryan. Duke University. Department of Physics, Durham, NC,; USA.
Fil: Cheng, Chao. New Jersey Institute of Technology. Department of Mathematical Sciences. Newark, NJ; USA.
Fil: Pugnaloni, Luis. Universidad Nacional de La Pampa, Departamento de Física, Facultad de Ciencias Exactas y Naturales. Consejo Nacional de Investigaciones Científicas y Técnicas, La Pampa, Argentina.
Fil: Kramár, Miroslav. University of Oklahoma. Department of Mathematics. Norman, OK; USA.
Fil: Zheng, Hu. Tongji University. College of Civil Engineering, Department of Geotechnical Engineering, Shanghai; China.
Fil: Socolar, Joshua E. S. Duke University. Department of Physics, Durham, NC,; USA.
Fil: Kondic, Lou. New Jersey Institute of Technology. Department of Mathematical Sciences. Newark, NJ; USA.
Peer Reviewed
arXiv:2102.12396v1 [cond-mat.soft] 24 Feb 2021
Materia
Granular flows
Jamming
Nivel de accesibilidad
acceso abierto
Condiciones de uso
2024-03-26T12:22:25Z
Repositorio
Repositorio Institucional Abierto (UTN)
Institución
Universidad Tecnológica Nacional
OAI Identificador
oai:ria.utn.edu.ar:20.500.12272/10089
Acceder
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spelling Two approaches to quantification of force networks in particulate systemsBasak, RituparnaCarlevaro, ManuelKozlowski, RyanCheng, ChaoPugnaloni, LuisKramár, MiroslavZheng, HuSocolar, Joshua E. S.Kondic, LouGranular flowsJammingThe interactions between particles in particulate systems are organized in ‘force networks’, mesoscale features that bridge between the particle scale and the scale of the system as a whole. While such networks are known to be crucial in determining the system wide response, extracting their properties, particularly from experimental systems, is difficult due to the need to measure the interparticle forces. In this work, we show by analysis of the data extracted from simulations that such detailed information about interparticle forces may not be necessary, as long as the focus is on extracting the most dominant features of these networks. The main finding is that a reasonable understanding of the time evolution of force networks can be obtained from incomplete information such as total force on the particles. To compare the evolution of the networks based on the completely known particle interactions and the networks based on incomplete information (total force each grain) we use tools of algebraic topology. In particular we will compare simple measures defined on persistence diagrams that provide useful summaries of the force network features. Fil: Basak, Rituparna. New Jersey Institute of Technology. Department of Mathematical Sciences. Newark, NJ; USA.Fil: Carlevaro, Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos. La Plata; Argentina.Fil: Carlevaro, Manuel. Universidad Tecnológica Nacional. Facultad Regional La Plata. Departamento de Ingeniería Mecánica; Argentina.Fil: Kozlowski, Ryan. Duke University. Department of Physics, Durham, NC,; USA.Fil: Cheng, Chao. New Jersey Institute of Technology. Department of Mathematical Sciences. Newark, NJ; USA.Fil: Pugnaloni, Luis. Universidad Nacional de La Pampa, Departamento de Física, Facultad de Ciencias Exactas y Naturales. Consejo Nacional de Investigaciones Científicas y Técnicas, La Pampa, Argentina.Fil: Kramár, Miroslav. University of Oklahoma. Department of Mathematics. Norman, OK; USA.Fil: Zheng, Hu. Tongji University. College of Civil Engineering, Department of Geotechnical Engineering, Shanghai; China.Fil: Socolar, Joshua E. S. Duke University. Department of Physics, Durham, NC,; USA.Fil: Kondic, Lou. New Jersey Institute of Technology. Department of Mathematical Sciences. Newark, NJ; USA.Peer ReviewedarXiv:2102.12396v1 [cond-mat.soft] 24 Feb 20212024-03-26T12:22:25Z2024-03-26T12:22:25Z2021-02-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articulopdfapplication/pdfJournal of Engineering Mechanics--http://hdl.handle.net/20.500.12272/10089enginfo:eu-repo/semantics/openAccess2024-03-26T12:22:25Zhttp://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 InternacionalAtribución (Attribution): En cualquier explotación de la obra autorizada por la licencia será necesario reconocer la autoría (obligatoria en todos los casos). No comercial (Non Commercial): La explotación de la obra queda limitada a usos no comerciales. Sin obras derivadas (No Derivate Works): La autorización para explotar la obra no incluye la posibilidad de crear una obra derivada (traducciones, adaptaciones, etc.).reponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica Nacional2026-09-24T12:44:52Zoai:ria.utn.edu.ar:20.500.12272/10089instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-09-24 12:44:52.926Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse
dc.title.none.fl_str_mv Two approaches to quantification of force networks in particulate systems
title Two approaches to quantification of force networks in particulate systems
spellingShingle Two approaches to quantification of force networks in particulate systems
Basak, Rituparna
Granular flows
Jamming
title_short Two approaches to quantification of force networks in particulate systems
title_full Two approaches to quantification of force networks in particulate systems
title_fullStr Two approaches to quantification of force networks in particulate systems
title_full_unstemmed Two approaches to quantification of force networks in particulate systems
title_sort Two approaches to quantification of force networks in particulate systems
dc.creator.none.fl_str_mv Basak, Rituparna
Carlevaro, Manuel
Kozlowski, Ryan
Cheng, Chao
Pugnaloni, Luis
Kramár, Miroslav
Zheng, Hu
Socolar, Joshua E. S.
Kondic, Lou
author Basak, Rituparna
author_facet Basak, Rituparna
Carlevaro, Manuel
Kozlowski, Ryan
Cheng, Chao
Pugnaloni, Luis
Kramár, Miroslav
Zheng, Hu
Socolar, Joshua E. S.
Kondic, Lou
author_role author
author2 Carlevaro, Manuel
Kozlowski, Ryan
Cheng, Chao
Pugnaloni, Luis
Kramár, Miroslav
Zheng, Hu
Socolar, Joshua E. S.
Kondic, Lou
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Granular flows
Jamming
topic Granular flows
Jamming
dc.description.none.fl_txt_mv The interactions between particles in particulate systems are organized in ‘force networks’, mesoscale features that bridge between the particle scale and the scale of the system as a whole. While such networks are known to be crucial in determining the system wide response, extracting their properties, particularly from experimental systems, is difficult due to the need to measure the interparticle forces. In this work, we show by analysis of the data extracted from simulations that such detailed information about interparticle forces may not be necessary, as long as the focus is on extracting the most dominant features of these networks. The main finding is that a reasonable understanding of the time evolution of force networks can be obtained from incomplete information such as total force on the particles. To compare the evolution of the networks based on the completely known particle interactions and the networks based on incomplete information (total force each grain) we use tools of algebraic topology. In particular we will compare simple measures defined on persistence diagrams that provide useful summaries of the force network features.
Fil: Basak, Rituparna. New Jersey Institute of Technology. Department of Mathematical Sciences. Newark, NJ; USA.
Fil: Carlevaro, Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos. La Plata; Argentina.
Fil: Carlevaro, Manuel. Universidad Tecnológica Nacional. Facultad Regional La Plata. Departamento de Ingeniería Mecánica; Argentina.
Fil: Kozlowski, Ryan. Duke University. Department of Physics, Durham, NC,; USA.
Fil: Cheng, Chao. New Jersey Institute of Technology. Department of Mathematical Sciences. Newark, NJ; USA.
Fil: Pugnaloni, Luis. Universidad Nacional de La Pampa, Departamento de Física, Facultad de Ciencias Exactas y Naturales. Consejo Nacional de Investigaciones Científicas y Técnicas, La Pampa, Argentina.
Fil: Kramár, Miroslav. University of Oklahoma. Department of Mathematics. Norman, OK; USA.
Fil: Zheng, Hu. Tongji University. College of Civil Engineering, Department of Geotechnical Engineering, Shanghai; China.
Fil: Socolar, Joshua E. S. Duke University. Department of Physics, Durham, NC,; USA.
Fil: Kondic, Lou. New Jersey Institute of Technology. Department of Mathematical Sciences. Newark, NJ; USA.
Peer Reviewed
arXiv:2102.12396v1 [cond-mat.soft] 24 Feb 2021
description The interactions between particles in particulate systems are organized in ‘force networks’, mesoscale features that bridge between the particle scale and the scale of the system as a whole. While such networks are known to be crucial in determining the system wide response, extracting their properties, particularly from experimental systems, is difficult due to the need to measure the interparticle forces. In this work, we show by analysis of the data extracted from simulations that such detailed information about interparticle forces may not be necessary, as long as the focus is on extracting the most dominant features of these networks. The main finding is that a reasonable understanding of the time evolution of force networks can be obtained from incomplete information such as total force on the particles. To compare the evolution of the networks based on the completely known particle interactions and the networks based on incomplete information (total force each grain) we use tools of algebraic topology. In particular we will compare simple measures defined on persistence diagrams that provide useful summaries of the force network features.
publishDate 2021
dc.date.none.fl_str_mv 2021-02-24
2024-03-26T12:22:25Z
2024-03-26T12:22:25Z
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 Journal of Engineering Mechanics
--
http://hdl.handle.net/20.500.12272/10089
identifier_str_mv Journal of Engineering Mechanics
--
url http://hdl.handle.net/20.500.12272/10089
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
2024-03-26T12:22:25Z
http://creativecommons.org/licenses/by-nc-nd/4.0/
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Atribución (Attribution): En cualquier explotación de la obra autorizada por la licencia será necesario reconocer la autoría (obligatoria en todos los casos). No comercial (Non Commercial): La explotación de la obra queda limitada a usos no comerciales. Sin obras derivadas (No Derivate Works): La autorización para explotar la obra no incluye la posibilidad de crear una obra derivada (traducciones, adaptaciones, etc.).
eu_rights_str_mv openAccess
rights_invalid_str_mv 2024-03-26T12:22:25Z
http://creativecommons.org/licenses/by-nc-nd/4.0/
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Atribución (Attribution): En cualquier explotación de la obra autorizada por la licencia será necesario reconocer la autoría (obligatoria en todos los casos). No comercial (Non Commercial): La explotación de la obra queda limitada a usos no comerciales. Sin obras derivadas (No Derivate Works): La autorización para explotar la obra no incluye la posibilidad de crear una obra derivada (traducciones, adaptaciones, etc.).
dc.format.none.fl_str_mv pdf
application/pdf
dc.source.none.fl_str_mv reponame:Repositorio Institucional Abierto (UTN)
instname:Universidad Tecnológica Nacional
reponame_str Repositorio Institucional Abierto (UTN)
collection Repositorio Institucional Abierto (UTN)
instname_str Universidad Tecnológica Nacional
repository.name.fl_str_mv Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacional
repository.mail.fl_str_mv gestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.ar
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score 13.265058

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