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Risk-based decision-making for system-level fatigue assessment of bridges
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Structural Engineering and Bridges.ORCID iD: 0000-0003-3244-1153
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Structural Engineering and Bridges.ORCID iD: 0000-0002-2833-4585
2023 (English)In: Engineering Failure Analysis, ISSN 1350-6307, E-ISSN 1873-1961, Vol. 153, article id 107533Article in journal (Refereed) Published
Abstract [en]

Fatigue is among the most decisive degradation phenomena that can potentially occur in steel bridges. However, accurate assessments of the fatigue damage and optimal decision-making based on these assessments are still challenging. This paper aims to present a study on decision-making for existing fatigue-sensitive bridges. It includes a discussion about different assessment methods and acceptance criteria; this discussion concerns whether similar decisions can be made using reliability-based analysis and risk-based analysis, respectively. Different system setups have also been studied to determine their impact on decision-making. Probabilistic fatigue assessment is used as the basis of the study, and a utility-based decision analysis is used to evaluate possible action alternatives to extend the service life of an existing bridge. The decision scenarios are established by considering the associated consequences and potential costs.

A general application and a selected critical railway bridge are utilised to demonstrate the framework. The study shows that system setups directly impact the system reliability and further lead to different optimal decisions. Additionally, when the probability of failure due to fatigue is low to a certain extent, local fatigue will not greatly influence the failure of the whole bridge or the optimal decision.

Place, publisher, year, edition, pages
Elsevier BV , 2023. Vol. 153, article id 107533
National Category
Civil Engineering
Identifiers
URN: urn:nbn:se:kth:diva-335403DOI: 10.1016/j.engfailanal.2023.107533ISI: 001068760600001Scopus ID: 2-s2.0-85169299049OAI: oai:DiVA.org:kth-335403DiVA, id: diva2:1794804
Note

QC 20230906

Available from: 2023-09-06 Created: 2023-09-06 Last updated: 2023-10-09Bibliographically approved

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Wang, RuoqiLeander, John

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CiteExportLink to record
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