Probabilistic assessment of the depassivation limit state of reinforced concrete structures based on inspection results
The aging of our concrete structures has led to a growing need to assess their actual condition, not only for maintenance purposes, but also to plan the extension of their service life. Today, only few methods that use inspection data can be found in the literature for performing that assessment, an...
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Veröffentlicht in: | Journal of Building Engineering 2022-05, Vol.49, p.104063, Article 104063 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The aging of our concrete structures has led to a growing need to assess their actual condition, not only for maintenance purposes, but also to plan the extension of their service life. Today, only few methods that use inspection data can be found in the literature for performing that assessment, and are usually based on the Bayesian probability theory, which requires prior information on the structures condition and often demands specific statistical knowledge and software that are not familiar to most practitioners. In this article, a probabilistic methodology based on a frequentist approach is presented for assessing the limit state of depassivation of concrete structures, using inspection results on cover depth, carbonation depth and depth of critical chloride content. It introduces the concept of passivation curve, which depicts the confidence of the estimated percentage of passivated steel bars, providing a valuable tool for supporting the decision-making for the life-cycle management of concrete structures. Its application is demonstrated using the inspection data from five real structures up to 41 years old. This article also discusses the experimental and code requirements for the condition assessment of concrete structures and the physical interpretation of the probability of passivation in the context of inspection. The relevance of experimental conditions for the determination of the critical chloride content of concrete is highlighted, as well as the urgent need to get data on its in situ distribution. |
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ISSN: | 2352-7102 2352-7102 |
DOI: | 10.1016/j.jobe.2022.104063 |