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Structure and Infrastructure Engineering
Maintenance, Management, Life-Cycle Design and Performance
Volume 10, 2014 - Issue 8
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Original Articles

Corrosion initiation time updating by epistemic uncertainty as an alternative to schedule the first inspection time of pre-stressed concrete vehicular bridge beams

, , , &
Pages 998-1010 | Received 17 Mar 2012, Accepted 07 Jan 2013, Published online: 09 Apr 2013
 

Abstract

As traffic demands grow constantly and some vehicle bridges deteriorate because of corrosion issues, bridge agencies require non-expensive procedures to support decisions about cost-effective maintenance schedules. In this article, a reliability-based formulation is proposed for the prediction of the optimal first inspection time including both the corrosion deterioration and the epistemic uncertainty on the corrosion initiation time. For the identification of the bridge integrity state, where little or no follow-up has been previously developed, the prediction of a damage state implies a great deal of epistemic uncertainty. The impact of this kind of uncertainty on the corrosion initiation time prediction is appraised in order to include the conservative estimations of such a time, according to the bridge revenues/cost ratio of further and more detailed studies. The time-varying bridge reliability is calculated in terms of the bridge corrosion deterioration, which induces a moment capacity reduction of the bridge beams. Epistemic uncertainty is introduced in the corrosion initiation time, and the optimal first inspection time is obtained as a probability distribution. Consequently, a procedure to calculate the first time for inspection on girder bridges has been proposed, based on updating a known distribution after considering the effect of epistemic uncertainty, using a lognormal distributed factor as ‘evidence’, by means of the Markov chain Monte Carlo technique.

Acknowledgements

The authors thank UAEM for the financial support to conduct this research throughout project 3376/2012 CA. The authors also thank the National Council for Science and Technology (CONACYT projects 158225 & 145462), for the provided support.

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