Predicting the Corrosion Initiation Time in Reinforced Concrete Bridges Using Stochastic Simulation Methods

Reinforced Concrete Bridges are considered one of the main components of the transportation infrastructure. These bridges require regular inspection and maintenance in order to be able to carry the applied loads. Predicting the behavior of concrete bridges and the time their condition state changes is crucial for providing better bridge management. Corrosion is considered one of the main reasons behind bridge deterioration. In this paper the time of corrosion initiation and the probability of exceeding a critical chloride level in the concrete substrate is evaluated, using Stochastic simulation methods. A probabilistic analysis was done considering the uncertainty associated with a corrosion initiation prediction model and associated parameters. The analysis process was divided into three main stages. In stage 1, Monte Carlo Simulation (MCS), Importance Sampling (IS) and Taylor Expansion Series were used to predict the corrosion initiation time. In stage 2 the probability to exceed the chloride threshold level was considered as the probability of failure and was estimated at different time periods using Monte Carlo Simulation (MCS), Importance Sampling (IS) and First Order Reliability Method (FORM). Finally, in stage 3 model parameters were updated using Bayesian updating. Inspection data measurements were assumed for the updating process.

Keywords: Reinforced concrete bridges, Chloride induced corrosion, Monte carlo simulation (MCS), First order reliability method (FORM), Importance sampling (IS), Taylor expansion series, Bayesian updating