Keywords
Reinforce concrete, corrosion, cover cracking, probability model, Monte Carlo simulation
Abstract
Corrosion-induced concrete cover cracking caused by chloride ion is an important indication of durability limit state for marine reinforced concrete (RC) structures and can ultimately determine the structural service life. In this paper, considering the random nature of factors affecting the corrosion cracking process, a probabilistic model which expands on the deterministic model of cover cracking time is developed by using Monte Carlo simulation technique. The results showed that the time to corrosion cracking can be modelled by the Weibull distribution. Finally, the probabilistic analysis for the cracking time is applied to an in-site RC bridge girder with four different durability design specifications. It is found that the mean and 90% confidence interval of the cover cracking time will increase with the improvement of durability design level, which means that the difficulty in precise prediction with deterministic model will augment accordingly.
DOI
10.5703/1288284316150
Included in
Probability Model of Corrosion-Induced Cracking Time in Chloride-Contaminated Reinforced Concrete
Corrosion-induced concrete cover cracking caused by chloride ion is an important indication of durability limit state for marine reinforced concrete (RC) structures and can ultimately determine the structural service life. In this paper, considering the random nature of factors affecting the corrosion cracking process, a probabilistic model which expands on the deterministic model of cover cracking time is developed by using Monte Carlo simulation technique. The results showed that the time to corrosion cracking can be modelled by the Weibull distribution. Finally, the probabilistic analysis for the cracking time is applied to an in-site RC bridge girder with four different durability design specifications. It is found that the mean and 90% confidence interval of the cover cracking time will increase with the improvement of durability design level, which means that the difficulty in precise prediction with deterministic model will augment accordingly.
