Multiscale Characterisation of Cortical Bone Tissue

Multiscale analysis has become an attractive technique to predict the behaviour of materials whose microstructure strongly changes spatially or among samples, with that microstructure controlling the local constitutive behaviour. This is the case, for example, of most biological tissues—such as bone...

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Autores: Sanz Herrera, José Antonio, Mora Macías, Juan, Reina Romo, Esther, Domínguez Abascal, Jaime, Doblaré, M.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/99402
Acceso en línea:https://hdl.handle.net/11441/99402
https://doi.org/10.3390/app9235228
Access Level:acceso abierto
Palabra clave:Cortical bone
Digital image correlation
Multiscale analysis
Micromechanics
Computational mechanics
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spelling Multiscale Characterisation of Cortical Bone TissueSanz Herrera, José AntonioMora Macías, JuanReina Romo, EstherDomínguez Abascal, JaimeDoblaré, M.Cortical boneDigital image correlationMultiscale analysisMicromechanicsComputational mechanicsMultiscale analysis has become an attractive technique to predict the behaviour of materials whose microstructure strongly changes spatially or among samples, with that microstructure controlling the local constitutive behaviour. This is the case, for example, of most biological tissues—such as bone. Multiscale approaches not only allow, not only to better characterise the local behaviour, but also to predict the field-variable distributions (e.g., strains, stresses) at both scales (macro and micro) simultaneously. However, multiscale analysis usually lacks su cient experimental feedback to demonstrate its validity. In this paper an experimental and numerical micromechanics analysis is developed with application to cortical bone. Displacement and strain fields are obtained across the microstructure by means of digital image correlation (DIC). The other mechanical variables are computed following the micromechanics theory. Special emphasis is given to the di erences found in the di erent field variables between the micro- and macro-structures, which points out the need for this multiscale approach in cortical bone tissue. The obtained results are used to establish the basis of a multiscale methodology with application to the analysis of bone tissue mechanics at di erent spatial scales.Ministerio de Economía y Competitividad DPI2014-58233-PMinisterio de Economía y Competitividad DPI2017-82501-PMinisterio de Economía y Competitividad PGC2018-097257-B-C31MDPIMecánica de Medios Continuos y Teoría de EstructurasIngeniería Mecánica y FabricaciónMinisterio de Economía y Competitividad (MINECO). España2019info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/99402https://doi.org/10.3390/app9235228reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésApplied Sciences, 9 (23), Article number 5228.DPI2014-58233-PDPI2017-82501-PPGC2018-097257-B-C31https://doi.org/10.3390/app9235228info:eu-repo/semantics/openAccessoai:idus.us.es:11441/994022026-06-17T12:51:07Z
dc.title.none.fl_str_mv Multiscale Characterisation of Cortical Bone Tissue
title Multiscale Characterisation of Cortical Bone Tissue
spellingShingle Multiscale Characterisation of Cortical Bone Tissue
Sanz Herrera, José Antonio
Cortical bone
Digital image correlation
Multiscale analysis
Micromechanics
Computational mechanics
title_short Multiscale Characterisation of Cortical Bone Tissue
title_full Multiscale Characterisation of Cortical Bone Tissue
title_fullStr Multiscale Characterisation of Cortical Bone Tissue
title_full_unstemmed Multiscale Characterisation of Cortical Bone Tissue
title_sort Multiscale Characterisation of Cortical Bone Tissue
dc.creator.none.fl_str_mv Sanz Herrera, José Antonio
Mora Macías, Juan
Reina Romo, Esther
Domínguez Abascal, Jaime
Doblaré, M.
author Sanz Herrera, José Antonio
author_facet Sanz Herrera, José Antonio
Mora Macías, Juan
Reina Romo, Esther
Domínguez Abascal, Jaime
Doblaré, M.
author_role author
author2 Mora Macías, Juan
Reina Romo, Esther
Domínguez Abascal, Jaime
Doblaré, M.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Mecánica de Medios Continuos y Teoría de Estructuras
Ingeniería Mecánica y Fabricación
Ministerio de Economía y Competitividad (MINECO). España
dc.subject.none.fl_str_mv Cortical bone
Digital image correlation
Multiscale analysis
Micromechanics
Computational mechanics
topic Cortical bone
Digital image correlation
Multiscale analysis
Micromechanics
Computational mechanics
description Multiscale analysis has become an attractive technique to predict the behaviour of materials whose microstructure strongly changes spatially or among samples, with that microstructure controlling the local constitutive behaviour. This is the case, for example, of most biological tissues—such as bone. Multiscale approaches not only allow, not only to better characterise the local behaviour, but also to predict the field-variable distributions (e.g., strains, stresses) at both scales (macro and micro) simultaneously. However, multiscale analysis usually lacks su cient experimental feedback to demonstrate its validity. In this paper an experimental and numerical micromechanics analysis is developed with application to cortical bone. Displacement and strain fields are obtained across the microstructure by means of digital image correlation (DIC). The other mechanical variables are computed following the micromechanics theory. Special emphasis is given to the di erences found in the di erent field variables between the micro- and macro-structures, which points out the need for this multiscale approach in cortical bone tissue. The obtained results are used to establish the basis of a multiscale methodology with application to the analysis of bone tissue mechanics at di erent spatial scales.
publishDate 2019
dc.date.none.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/99402
https://doi.org/10.3390/app9235228
url https://hdl.handle.net/11441/99402
https://doi.org/10.3390/app9235228
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Applied Sciences, 9 (23), Article number 5228.
DPI2014-58233-P
DPI2017-82501-P
PGC2018-097257-B-C31
https://doi.org/10.3390/app9235228
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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