Prediction of the mechanical properties of timber members in existing structures using the dynamic modulus of elasticity and visual grading parameters

The modulus of elasticity and bending strength of 45 structural Salzmann pine timber pieces with nominal dimensions of 150x200x5400 mm3 from an existing 18th century structure were estimated by semi-destructive density estimation probing method (drilling chips extraction) and acoustic wave velocity...

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Detalles Bibliográficos
Autores: Arriaga, Francisco, Osuna-Sequera, Carlos, Bobadilla, Ignacio, Esteban, Miguel
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/289623
Acceso en línea:http://hdl.handle.net/10261/289623
Access Level:acceso abierto
Palabra clave:Bending strength
Existing structures
In-situ assessment
MOE
MOR
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spelling Prediction of the mechanical properties of timber members in existing structures using the dynamic modulus of elasticity and visual grading parametersArriaga, FranciscoOsuna-Sequera, CarlosBobadilla, IgnacioEsteban, MiguelBending strengthExisting structuresIn-situ assessmentMOEMORThe modulus of elasticity and bending strength of 45 structural Salzmann pine timber pieces with nominal dimensions of 150x200x5400 mm3 from an existing 18th century structure were estimated by semi-destructive density estimation probing method (drilling chips extraction) and acoustic wave velocity (stress and ultrasound wave). Bending strength, modulus of elasticity and density were obtained according to the EN 408 European standard, and visual grading singularities were recorded. Visual grading methods are highly ineffective for existing timber structures. Sample mechanical properties show a typical profile of material from existing structures, and this was compared with the results of similar works. MOE and MOR predictive models were proposed with determination coefficients r2 of 66–68% and 51–52%, respectively, using dynamic MOE, relative edge knot diameter and slope of grain as independent variables. MOR prediction improved when these grading parameters were included.ElsevierEsteban, Miguel [0000-0003-3364-9044]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202320232022info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501http://hdl.handle.net/10261/289623reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)InglésInstituto de Ciencias Forestales (ICIFOR)Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2896232026-05-22T06:33:51Z
dc.title.none.fl_str_mv Prediction of the mechanical properties of timber members in existing structures using the dynamic modulus of elasticity and visual grading parameters
title Prediction of the mechanical properties of timber members in existing structures using the dynamic modulus of elasticity and visual grading parameters
spellingShingle Prediction of the mechanical properties of timber members in existing structures using the dynamic modulus of elasticity and visual grading parameters
Arriaga, Francisco
Bending strength
Existing structures
In-situ assessment
MOE
MOR
title_short Prediction of the mechanical properties of timber members in existing structures using the dynamic modulus of elasticity and visual grading parameters
title_full Prediction of the mechanical properties of timber members in existing structures using the dynamic modulus of elasticity and visual grading parameters
title_fullStr Prediction of the mechanical properties of timber members in existing structures using the dynamic modulus of elasticity and visual grading parameters
title_full_unstemmed Prediction of the mechanical properties of timber members in existing structures using the dynamic modulus of elasticity and visual grading parameters
title_sort Prediction of the mechanical properties of timber members in existing structures using the dynamic modulus of elasticity and visual grading parameters
dc.creator.none.fl_str_mv Arriaga, Francisco
Osuna-Sequera, Carlos
Bobadilla, Ignacio
Esteban, Miguel
author Arriaga, Francisco
author_facet Arriaga, Francisco
Osuna-Sequera, Carlos
Bobadilla, Ignacio
Esteban, Miguel
author_role author
author2 Osuna-Sequera, Carlos
Bobadilla, Ignacio
Esteban, Miguel
author2_role author
author
author
dc.contributor.none.fl_str_mv Esteban, Miguel [0000-0003-3364-9044]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Bending strength
Existing structures
In-situ assessment
MOE
MOR
topic Bending strength
Existing structures
In-situ assessment
MOE
MOR
description The modulus of elasticity and bending strength of 45 structural Salzmann pine timber pieces with nominal dimensions of 150x200x5400 mm3 from an existing 18th century structure were estimated by semi-destructive density estimation probing method (drilling chips extraction) and acoustic wave velocity (stress and ultrasound wave). Bending strength, modulus of elasticity and density were obtained according to the EN 408 European standard, and visual grading singularities were recorded. Visual grading methods are highly ineffective for existing timber structures. Sample mechanical properties show a typical profile of material from existing structures, and this was compared with the results of similar works. MOE and MOR predictive models were proposed with determination coefficients r2 of 66–68% and 51–52%, respectively, using dynamic MOE, relative edge knot diameter and slope of grain as independent variables. MOR prediction improved when these grading parameters were included.
publishDate 2022
dc.date.none.fl_str_mv 2022
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/289623
url http://hdl.handle.net/10261/289623
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Instituto de Ciencias Forestales (ICIFOR)
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869411980085821440
score 15,198674

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