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International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP) (12th : 2015)
Probabilistic fatigue life prediction for bridges using system reliability analysis and SHM-based finite element model updating Lee, Young-Joo; Cho, Soojin
Abstract
Fatigue is one of the main causes of bridge failures. A bridge is designed with a particular service life, but after it is constructed, its strength degrades over time. Therefore, to effectively maintain and retrofit a bridge, it is essential to predict its remaining fatigue life. However, doing so is a very challenging task because fatigue life prediction should be based on the current condition of the bridge, and this obviously incurs many uncertainties. In addition, fatigue life prediction should be performed at the system level to take the structural redundancy of a bridge into account. This paper proposes a new approach based on the probabilistic fatigue life prediction of bridges using finite element (FE) model updating based on structural health monitoring (SHM) data. The proposed method involves three steps: (1) identifying the modal parameters of a bridge, such as the natural frequencies and mode shapes, from the ambient vibration under the influence of passing vehicles; (2) updating the structural parameters of an initial FE model using the identified modal parameters; and (3) predicting the probabilistic fatigue life at the system level by employing the updated FE model. The proposed method is applied to a numerical bridge example, and the analysis results are verified by comparing them with the results obtained from a Monte Carlo simulation.
Item Metadata
Title |
Probabilistic fatigue life prediction for bridges using system reliability analysis and SHM-based finite element model updating
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Creator | |
Contributor | |
Date Issued |
2015-07
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Description |
Fatigue is one of the main causes of bridge failures. A bridge is designed with a
particular service life, but after it is constructed, its strength degrades over time. Therefore, to
effectively maintain and retrofit a bridge, it is essential to predict its remaining fatigue life. However,
doing so is a very challenging task because fatigue life prediction should be based on the current
condition of the bridge, and this obviously incurs many uncertainties. In addition, fatigue life prediction
should be performed at the system level to take the structural redundancy of a bridge into account. This
paper proposes a new approach based on the probabilistic fatigue life prediction of bridges using finite
element (FE) model updating based on structural health monitoring (SHM) data. The proposed method
involves three steps: (1) identifying the modal parameters of a bridge, such as the natural frequencies
and mode shapes, from the ambient vibration under the influence of passing vehicles; (2) updating the
structural parameters of an initial FE model using the identified modal parameters; and (3) predicting
the probabilistic fatigue life at the system level by employing the updated FE model. The proposed
method is applied to a numerical bridge example, and the analysis results are verified by comparing
them with the results obtained from a Monte Carlo simulation.
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Type | |
Language |
eng
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Notes |
This collection contains the proceedings of ICASP12, the 12th International Conference on Applications of Statistics and Probability in Civil Engineering held in Vancouver, Canada on July 12-15, 2015. Abstracts were peer-reviewed and authors of accepted abstracts were invited to submit full papers. Also full papers were peer reviewed. The editor for this collection is Professor Terje Haukaas, Department of Civil Engineering, UBC Vancouver.
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Date Available |
2015-05-20
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivs 2.5 Canada
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DOI |
10.14288/1.0076079
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URI | |
Affiliation | |
Citation |
Haukaas, T. (Ed.) (2015). Proceedings of the 12th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP12), Vancouver, Canada, July 12-15.
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Peer Review Status |
Unreviewed
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Scholarly Level |
Researcher
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DSpace
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Rights
Attribution-NonCommercial-NoDerivs 2.5 Canada