Structural Health Monitoring Based Time- Dependent Reliabilityanalysis of Concrete Bridge
The presence of chloride ions in concrete is the most important cause of steel reinforcing corrosion. Corrosion can lead to structural damage and needs to be managed effectively for better allocation of resources and effective bridge management. The application of de-icing salt or atmospheric exposu...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/3021/ http://umpir.ump.edu.my/id/eprint/3021/2/KHAIRUL_ANUAR_SHAHID_AICCE_2012.pdf |
| Summary: | The presence of chloride ions in concrete is the most important cause of steel reinforcing corrosion. Corrosion can lead to structural damage and needs to be managed effectively for better allocation of resources and effective bridge management. The application of de-icing salt or atmospheric exposure in marine environment could be the cause of corrosion initiation. This paper reviews chloride ingress prediction model and presents methodology to improve confidence in predicting corrosion concentration taking into account time dependent reliability analysis. Modeling uncertainty is often associated with limited knowledge which it can be reduced by increasing the availability of data. Additional information through bridge inspection and monitoring will increase confidence in prediction models. Monte Carlo simulation with Latin Hypercube Sampling is used to estimate prior and posterior performance prediction for chloride concentration. Bayesian Updating is used to incorporate prior beliefs about the condition and performance of the bridge together with data obtained through inspections and health monitoring to produce more quantitative data. The application of Bayesian Updating is shown to considerably reduce uncertainties associated with performance prediction. By using this approach, it will lead to the prediction of structural performance with increased confidence. |
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