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Title |
A Long-term Durability Prediction for RC Structures Exposed to Carbonation Using Probabilistic Approach
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Keywords |
내구성 예측 ; 탄산화 ; 베이스 이론 ; 라틴 하이퍼큐브 샘플링 기법 ; 잔존수명 Durability Prediction ; Carbonation ; Bayes' theorem ; LHS Technique ; Remaining Service Life |
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Abstract |
This paper provides a new approach for durability prediction of reinforced concrete structures exposed to carbonation. In this method, the prediction can be updated successively by a Bayes' theorem when additional data are available. The stochastic properties of model parameters are explicitly taken into account in the model. To simplify the procedure of the model, the probability of the durability limit is determined based on the samples obtained from the Latin Hypercube Sampling(LHS) technique. The new method may be very useful in design of important concrete structures and help to predict the remaining service life of existing concrete structures which have been monitored. For using the new method, in which the prior distribution is developed to represent the uncertainties of the carbonation velocity using data of concrete structures(3700 specimens) in Korea and the likelihood function is used to monitor in-situ data. The posterior distribution is obtained by combining a prior distribution and a likelihood function. Efficiency of the LHS technique for simulation was confirmed through a comparison between the LHS and the Monte Calro Simulation(MCS) technique.
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