Durability Monitoring for Improved Service Life Predictions of Concrete Bridge Decks in Corrosive Environments

The development of an effective strategy for the inspection and monitoring of the nation's critical bridges has become necessary due to aging, increased traffic loads, changing environmental conditions, and advanced deterioration. This article presents the development of a probabilistic mechanistic modeling approach supported by durability monitoring to obtain improved predictions of service life of concrete bridge decks exposed to chlorides. The application and benefits of this approach are illustrated on a case study of a reinforced concrete barrier wall of a highway bridge monitored over 10 years. It is demonstrated that service life predictions using probabilistic models calibrated with selected monitored field data can provide more reliable assessments of the probabilities of reinforcement corrosion and corrosion-induced damage compared to using deterministic models based on standard data from the literature. Such calibrated probabilistic models can help decision makers optimize intervention strategies as to how and when to repair or rehabilitate a given structure, thus improving its life cycle performance, extending its service life and reducing its life cycle cost.