Due to the existence of uncertainties associated with mechanical properties, geometric configuration, loadings, and imperfect knowledge associated with the evaluations and predictions of material deterioration, probabilistic methods have been applied in the design and performance assessment of concrete structures to quantify these unavoidable uncertainties. This paper presents an approach for improving the accuracy in the life-cycle reliability assessment of reinforced concrete (RC) structures subjected to the carbonation by the Sequential Monte Carlo Simulation (SMCS). Using SMCS, multiple random variables related to observation information can be updated simultaneously, even if non-Gaussian random variables are involved and relationships between the observation information and random variables are nonlinear. The effect of the magnitude of inspected carbonation depth on the updated estimates of reliability associated with the occurrence of steel corrosion is discussed in this paper.
|Sustainable Construction Materials and Technologies
|Published - 2013 1月 1
|3rd International Conference on Sustainable Construction Materials and Technologies, SCMT 2013 - Kyoto, Japan
継続期間: 2013 8月 18 → 2013 8月 21
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