Condition prediction of existing concrete bridges as a combination of visual inspection and analytical models of deterioration
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/59001 |
Resumo: | In most state-of-the-art Bridge Management Systems, structural condition is predicted by a homogeneous Markov chain model that uses condition ratings assigned during visual inspections. Although generally accepted, such an approach exhibits certain shortcomings, one of which is not considering the nature of actual physical phenomena that cause deterioration. To overcome this shortcoming, this article presents a framework that combines both information on condition ratings through the semi-Markov process and knowledge of bridge properties using analytical deterioration models. In this manner, and contrary to current practice, not only are the results of visual inspection taken into account, but also information such as environmental loading, as well as material and structural properties. The presented framework was implemented in the case study bridge, in which the deterioration caused by carbonation-induced corrosion was studied. Along with the implementation in the case study, the article contained a detailed overview of the subject of carbonation-induced corrosion and emphasized issues that require additional research in order to develop the framework into a comprehensive and fully applicable tool for condition prediction. Accounting for its adaptability to other material types and deterioration processes and its consideration of the historic deterioration path, the framework presents a suitable alternative to frameworks presently implemented for condition prediction |
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Condition prediction of existing concrete bridges as a combination of visual inspection and analytical models of deteriorationConcrete bridgesCondition predictionBridge management systemsemi-Markov processMarkov chainCarbonation-induced corrosionStructural performanceDeteriorationEngenharia e Tecnologia::Engenharia CivilScience & TechnologyIn most state-of-the-art Bridge Management Systems, structural condition is predicted by a homogeneous Markov chain model that uses condition ratings assigned during visual inspections. Although generally accepted, such an approach exhibits certain shortcomings, one of which is not considering the nature of actual physical phenomena that cause deterioration. To overcome this shortcoming, this article presents a framework that combines both information on condition ratings through the semi-Markov process and knowledge of bridge properties using analytical deterioration models. In this manner, and contrary to current practice, not only are the results of visual inspection taken into account, but also information such as environmental loading, as well as material and structural properties. The presented framework was implemented in the case study bridge, in which the deterioration caused by carbonation-induced corrosion was studied. Along with the implementation in the case study, the article contained a detailed overview of the subject of carbonation-induced corrosion and emphasized issues that require additional research in order to develop the framework into a comprehensive and fully applicable tool for condition prediction. Accounting for its adaptability to other material types and deterioration processes and its consideration of the historic deterioration path, the framework presents a suitable alternative to frameworks presently implemented for condition prediction(undefined)info:eu-repo/semantics/publishedVersionMDPI PublishingUniversidade do MinhoZambon, I.Vidovic, A.Strauss, A.Matos, José C.2019-012019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/59001engZambon, I., Vidović, A., Strauss, A., & Matos, J. (2019). Condition Prediction of Existing Concrete Bridges as a Combination of Visual Inspection and Analytical Models of Deterioration. Applied Sciences, 9(1), 1482076-34172076-341710.3390/app9010148https://www.mdpi.com/2076-3417/9/1/148info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:28:15Zoai:repositorium.sdum.uminho.pt:1822/59001Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:23:01.629476Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Condition prediction of existing concrete bridges as a combination of visual inspection and analytical models of deterioration |
title |
Condition prediction of existing concrete bridges as a combination of visual inspection and analytical models of deterioration |
spellingShingle |
Condition prediction of existing concrete bridges as a combination of visual inspection and analytical models of deterioration Zambon, I. Concrete bridges Condition prediction Bridge management system semi-Markov process Markov chain Carbonation-induced corrosion Structural performance Deterioration Engenharia e Tecnologia::Engenharia Civil Science & Technology |
title_short |
Condition prediction of existing concrete bridges as a combination of visual inspection and analytical models of deterioration |
title_full |
Condition prediction of existing concrete bridges as a combination of visual inspection and analytical models of deterioration |
title_fullStr |
Condition prediction of existing concrete bridges as a combination of visual inspection and analytical models of deterioration |
title_full_unstemmed |
Condition prediction of existing concrete bridges as a combination of visual inspection and analytical models of deterioration |
title_sort |
Condition prediction of existing concrete bridges as a combination of visual inspection and analytical models of deterioration |
author |
Zambon, I. |
author_facet |
Zambon, I. Vidovic, A. Strauss, A. Matos, José C. |
author_role |
author |
author2 |
Vidovic, A. Strauss, A. Matos, José C. |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Zambon, I. Vidovic, A. Strauss, A. Matos, José C. |
dc.subject.por.fl_str_mv |
Concrete bridges Condition prediction Bridge management system semi-Markov process Markov chain Carbonation-induced corrosion Structural performance Deterioration Engenharia e Tecnologia::Engenharia Civil Science & Technology |
topic |
Concrete bridges Condition prediction Bridge management system semi-Markov process Markov chain Carbonation-induced corrosion Structural performance Deterioration Engenharia e Tecnologia::Engenharia Civil Science & Technology |
description |
In most state-of-the-art Bridge Management Systems, structural condition is predicted by a homogeneous Markov chain model that uses condition ratings assigned during visual inspections. Although generally accepted, such an approach exhibits certain shortcomings, one of which is not considering the nature of actual physical phenomena that cause deterioration. To overcome this shortcoming, this article presents a framework that combines both information on condition ratings through the semi-Markov process and knowledge of bridge properties using analytical deterioration models. In this manner, and contrary to current practice, not only are the results of visual inspection taken into account, but also information such as environmental loading, as well as material and structural properties. The presented framework was implemented in the case study bridge, in which the deterioration caused by carbonation-induced corrosion was studied. Along with the implementation in the case study, the article contained a detailed overview of the subject of carbonation-induced corrosion and emphasized issues that require additional research in order to develop the framework into a comprehensive and fully applicable tool for condition prediction. Accounting for its adaptability to other material types and deterioration processes and its consideration of the historic deterioration path, the framework presents a suitable alternative to frameworks presently implemented for condition prediction |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01 2019-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/59001 |
url |
http://hdl.handle.net/1822/59001 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Zambon, I., Vidović, A., Strauss, A., & Matos, J. (2019). Condition Prediction of Existing Concrete Bridges as a Combination of Visual Inspection and Analytical Models of Deterioration. Applied Sciences, 9(1), 148 2076-3417 2076-3417 10.3390/app9010148 https://www.mdpi.com/2076-3417/9/1/148 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
MDPI Publishing |
publisher.none.fl_str_mv |
MDPI Publishing |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799132703265652736 |