A Stochastic Detection Models Comparison in Turbulent Flow Events

Autores
Calandra, Maria Valeria; Marañon Di Leo, Julio
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The need to establish the downwind fluid dynamic field of aerodynamic bodies subjected to a givenvelocity field is well known, to verify their aerodynamic characteristics. In this context, differenttechniques allow us to establish the characteristics of the field. It is almost always necessary to carry out quantitative determinations to describe the field correctly, particularly when the field is made up of turbulent wakes. In this sense, in the experimental field, it is common to use hot-wire anemometry techniques, which have great capabilities to quantify high-frequency events. Previous work has analyzed the determination of changes in hot-wire anemometry signals for the detection of events in turbulent flows with different models, based on stochastic algorithms (CPM - Change Point Model).The present work aims to compare the results obtained previously with the application of different CPM models developed. Previously applied and evaluated measurements are used, the implementation of the models is carried out and the results are compared. All the algorithms used can detect changes in data that do not have a known distribution, i.e. non-parametric distributions, which are typical for turbulent flow field signals. Measurements of the fluctuating components of the wind tunnel velocity at a specific point are considering. The signals used correspond to periodic detachments downstream of a flow control device (Gurney mini-flap) at the trailing edge of an airfoil. The results show which are the best models to use for the experimental detection of such turbulent events in the flow field.
Fil: Calandra, Maria Valeria. Universidad Nacional de La Plata. Facultad de Ingeniería; Argentina
Fil: Marañon Di Leo, Julio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ingeniería. Departamento de Aeronáutica. Laboratorio de Capa Límite y Fluído Dinámica Ambiental; Argentina
Materia
EVENT DETECTION
TURBULENT FLOW
VORTEX
CHANGE POINT MODELS
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:11336/227556
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/227556
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A Stochastic Detection Models Comparison in Turbulent Flow EventsCalandra, Maria ValeriaMarañon Di Leo, JulioEVENT DETECTIONTURBULENT FLOWVORTEXCHANGE POINT MODELShttps://purl.org/becyt/ford/2.3https://purl.org/becyt/ford/2The need to establish the downwind fluid dynamic field of aerodynamic bodies subjected to a givenvelocity field is well known, to verify their aerodynamic characteristics. In this context, differenttechniques allow us to establish the characteristics of the field. It is almost always necessary to carry out quantitative determinations to describe the field correctly, particularly when the field is made up of turbulent wakes. In this sense, in the experimental field, it is common to use hot-wire anemometry techniques, which have great capabilities to quantify high-frequency events. Previous work has analyzed the determination of changes in hot-wire anemometry signals for the detection of events in turbulent flows with different models, based on stochastic algorithms (CPM - Change Point Model).The present work aims to compare the results obtained previously with the application of different CPM models developed. Previously applied and evaluated measurements are used, the implementation of the models is carried out and the results are compared. All the algorithms used can detect changes in data that do not have a known distribution, i.e. non-parametric distributions, which are typical for turbulent flow field signals. Measurements of the fluctuating components of the wind tunnel velocity at a specific point are considering. The signals used correspond to periodic detachments downstream of a flow control device (Gurney mini-flap) at the trailing edge of an airfoil. The results show which are the best models to use for the experimental detection of such turbulent events in the flow field.Fil: Calandra, Maria Valeria. Universidad Nacional de La Plata. Facultad de Ingeniería; ArgentinaFil: Marañon Di Leo, Julio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ingeniería. Departamento de Aeronáutica. Laboratorio de Capa Límite y Fluído Dinámica Ambiental; ArgentinaSociety for Makers, Artists, Researchers and Technologists2023-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/227556Calandra, Maria Valeria; Marañon Di Leo, Julio; A Stochastic Detection Models Comparison in Turbulent Flow Events; Society for Makers, Artists, Researchers and Technologists; Journal of Mathematical Sciences & Computational Mathematics; 5; 1; 10-2023; 1-132688-83002644-3368CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://jmscm.smartsociety.org/vol5_issue1.htmlinfo:eu-repo/semantics/altIdentifier/doi/10.15864/jmscm.5101info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:47:20Zoai:ri.conicet.gov.ar:11336/227556instacron: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 09:47:20.71CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A Stochastic Detection Models Comparison in Turbulent Flow Events
title A Stochastic Detection Models Comparison in Turbulent Flow Events
spellingShingle A Stochastic Detection Models Comparison in Turbulent Flow Events
Calandra, Maria Valeria
EVENT DETECTION
TURBULENT FLOW
VORTEX
CHANGE POINT MODELS
title_short A Stochastic Detection Models Comparison in Turbulent Flow Events
title_full A Stochastic Detection Models Comparison in Turbulent Flow Events
title_fullStr A Stochastic Detection Models Comparison in Turbulent Flow Events
title_full_unstemmed A Stochastic Detection Models Comparison in Turbulent Flow Events
title_sort A Stochastic Detection Models Comparison in Turbulent Flow Events
dc.creator.none.fl_str_mv Calandra, Maria Valeria
Marañon Di Leo, Julio
author Calandra, Maria Valeria
author_facet Calandra, Maria Valeria
Marañon Di Leo, Julio
author_role author
author2 Marañon Di Leo, Julio
author2_role author
dc.subject.none.fl_str_mv EVENT DETECTION
TURBULENT FLOW
VORTEX
CHANGE POINT MODELS
topic EVENT DETECTION
TURBULENT FLOW
VORTEX
CHANGE POINT MODELS
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.3
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv The need to establish the downwind fluid dynamic field of aerodynamic bodies subjected to a givenvelocity field is well known, to verify their aerodynamic characteristics. In this context, differenttechniques allow us to establish the characteristics of the field. It is almost always necessary to carry out quantitative determinations to describe the field correctly, particularly when the field is made up of turbulent wakes. In this sense, in the experimental field, it is common to use hot-wire anemometry techniques, which have great capabilities to quantify high-frequency events. Previous work has analyzed the determination of changes in hot-wire anemometry signals for the detection of events in turbulent flows with different models, based on stochastic algorithms (CPM - Change Point Model).The present work aims to compare the results obtained previously with the application of different CPM models developed. Previously applied and evaluated measurements are used, the implementation of the models is carried out and the results are compared. All the algorithms used can detect changes in data that do not have a known distribution, i.e. non-parametric distributions, which are typical for turbulent flow field signals. Measurements of the fluctuating components of the wind tunnel velocity at a specific point are considering. The signals used correspond to periodic detachments downstream of a flow control device (Gurney mini-flap) at the trailing edge of an airfoil. The results show which are the best models to use for the experimental detection of such turbulent events in the flow field.
Fil: Calandra, Maria Valeria. Universidad Nacional de La Plata. Facultad de Ingeniería; Argentina
Fil: Marañon Di Leo, Julio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ingeniería. Departamento de Aeronáutica. Laboratorio de Capa Límite y Fluído Dinámica Ambiental; Argentina
description The need to establish the downwind fluid dynamic field of aerodynamic bodies subjected to a givenvelocity field is well known, to verify their aerodynamic characteristics. In this context, differenttechniques allow us to establish the characteristics of the field. It is almost always necessary to carry out quantitative determinations to describe the field correctly, particularly when the field is made up of turbulent wakes. In this sense, in the experimental field, it is common to use hot-wire anemometry techniques, which have great capabilities to quantify high-frequency events. Previous work has analyzed the determination of changes in hot-wire anemometry signals for the detection of events in turbulent flows with different models, based on stochastic algorithms (CPM - Change Point Model).The present work aims to compare the results obtained previously with the application of different CPM models developed. Previously applied and evaluated measurements are used, the implementation of the models is carried out and the results are compared. All the algorithms used can detect changes in data that do not have a known distribution, i.e. non-parametric distributions, which are typical for turbulent flow field signals. Measurements of the fluctuating components of the wind tunnel velocity at a specific point are considering. The signals used correspond to periodic detachments downstream of a flow control device (Gurney mini-flap) at the trailing edge of an airfoil. The results show which are the best models to use for the experimental detection of such turbulent events in the flow field.
publishDate 2023
dc.date.none.fl_str_mv 2023-10
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/11336/227556
Calandra, Maria Valeria; Marañon Di Leo, Julio; A Stochastic Detection Models Comparison in Turbulent Flow Events; Society for Makers, Artists, Researchers and Technologists; Journal of Mathematical Sciences & Computational Mathematics; 5; 1; 10-2023; 1-13
2688-8300
2644-3368
CONICET Digital
CONICET
url http://hdl.handle.net/11336/227556
identifier_str_mv Calandra, Maria Valeria; Marañon Di Leo, Julio; A Stochastic Detection Models Comparison in Turbulent Flow Events; Society for Makers, Artists, Researchers and Technologists; Journal of Mathematical Sciences & Computational Mathematics; 5; 1; 10-2023; 1-13
2688-8300
2644-3368
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://jmscm.smartsociety.org/vol5_issue1.html
info:eu-repo/semantics/altIdentifier/doi/10.15864/jmscm.5101
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 Society for Makers, Artists, Researchers and Technologists
publisher.none.fl_str_mv Society for Makers, Artists, Researchers and Technologists
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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