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International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP) (12th : 2015)
Bayesian updated time-dependent chloride-induced corrosion assessment using redundancy factors Botte, W.; Caspeele, R.; Taerwe, L.
Abstract
In order to assess the structural reliability and redundancy with respect to deterioration, it is required to select appropriate models which describe the deterioration process. The parameters associated with these models have to be estimated through statistical interference, which introduces uncertainties in parameter estimates. As the structural reliability indices which are incorporated in the reliability-based redundancy factor can be considered as random variable, this redundancy factor itself is a random variable as well. In case additional information becomes available, the distribution function can be updated by taking into account this extra information. In this contribution, a framework is developed, which allows for the incorporation of additional information in the uncertain reliability index and the associated redundancy factor through Bayesian updating. It is shown that in case additional information on a main variable is gathered, this has a significant effect on the (mean) value and uncertainty of the reliability index and the associated redundancy factor.
Item Metadata
Title |
Bayesian updated time-dependent chloride-induced corrosion assessment using redundancy factors
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Creator | |
Contributor | |
Date Issued |
2015-07
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Description |
In order to assess the structural reliability and redundancy with respect to deterioration, it is required to select appropriate models which describe the deterioration process. The parameters associated with these models have to be estimated through statistical interference, which introduces uncertainties in parameter estimates. As the structural reliability indices which are incorporated in the reliability-based redundancy factor can be considered as random variable, this redundancy factor itself is a random variable as well. In case additional information becomes available, the distribution function can be updated by taking into account this extra information. In this contribution, a framework is developed, which allows for the incorporation of additional information in the uncertain reliability index and the associated redundancy factor through Bayesian updating. It is shown that in case additional information on a main variable is gathered, this has a significant effect on the (mean) value and uncertainty of the reliability index and the associated redundancy factor.
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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 |
10.14288/1.0076133
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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 |
Faculty
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DSpace
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Rights
Attribution-NonCommercial-NoDerivs 2.5 Canada