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Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair

Railway bridges are exposed to repeated train loads, which may cause fatigue failure. As critical links in a transportation network, railway bridges are expected to survive for a target period of time, but sometimes they fail earlier than expected. To guarantee the target bridge life, bridge mainten...

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Autores principales: Lee, Young-Joo, Kim, Robin E., Suh, Wonho, Park, Kiwon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5426932/
https://www.ncbi.nlm.nih.gov/pubmed/28441768
http://dx.doi.org/10.3390/s17040936
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author Lee, Young-Joo
Kim, Robin E.
Suh, Wonho
Park, Kiwon
author_facet Lee, Young-Joo
Kim, Robin E.
Suh, Wonho
Park, Kiwon
author_sort Lee, Young-Joo
collection PubMed
description Railway bridges are exposed to repeated train loads, which may cause fatigue failure. As critical links in a transportation network, railway bridges are expected to survive for a target period of time, but sometimes they fail earlier than expected. To guarantee the target bridge life, bridge maintenance activities such as local inspection and repair should be undertaken properly. However, this is a challenging task because there are various sources of uncertainty associated with aging bridges, train loads, environmental conditions, and maintenance work. Therefore, to perform optimal risk-based maintenance of railway bridges, it is essential to estimate the probabilistic fatigue life of a railway bridge and update the life information based on the results of local inspections and repair. Recently, a system reliability approach was proposed to evaluate the fatigue failure risk of structural systems and update the prior risk information in various inspection scenarios. However, this approach can handle only a constant-amplitude load and has limitations in considering a cyclic load with varying amplitude levels, which is the major loading pattern generated by train traffic. In addition, it is not feasible to update the prior risk information after bridges are repaired. In this research, the system reliability approach is further developed so that it can handle a varying-amplitude load and update the system-level risk of fatigue failure for railway bridges after inspection and repair. The proposed method is applied to a numerical example of an in-service railway bridge, and the effects of inspection and repair on the probabilistic fatigue life are discussed.
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spelling pubmed-54269322017-05-12 Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair Lee, Young-Joo Kim, Robin E. Suh, Wonho Park, Kiwon Sensors (Basel) Article Railway bridges are exposed to repeated train loads, which may cause fatigue failure. As critical links in a transportation network, railway bridges are expected to survive for a target period of time, but sometimes they fail earlier than expected. To guarantee the target bridge life, bridge maintenance activities such as local inspection and repair should be undertaken properly. However, this is a challenging task because there are various sources of uncertainty associated with aging bridges, train loads, environmental conditions, and maintenance work. Therefore, to perform optimal risk-based maintenance of railway bridges, it is essential to estimate the probabilistic fatigue life of a railway bridge and update the life information based on the results of local inspections and repair. Recently, a system reliability approach was proposed to evaluate the fatigue failure risk of structural systems and update the prior risk information in various inspection scenarios. However, this approach can handle only a constant-amplitude load and has limitations in considering a cyclic load with varying amplitude levels, which is the major loading pattern generated by train traffic. In addition, it is not feasible to update the prior risk information after bridges are repaired. In this research, the system reliability approach is further developed so that it can handle a varying-amplitude load and update the system-level risk of fatigue failure for railway bridges after inspection and repair. The proposed method is applied to a numerical example of an in-service railway bridge, and the effects of inspection and repair on the probabilistic fatigue life are discussed. MDPI 2017-04-24 /pmc/articles/PMC5426932/ /pubmed/28441768 http://dx.doi.org/10.3390/s17040936 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lee, Young-Joo
Kim, Robin E.
Suh, Wonho
Park, Kiwon
Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair
title Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair
title_full Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair
title_fullStr Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair
title_full_unstemmed Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair
title_short Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair
title_sort probabilistic fatigue life updating for railway bridges based on local inspection and repair
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5426932/
https://www.ncbi.nlm.nih.gov/pubmed/28441768
http://dx.doi.org/10.3390/s17040936
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