Improving performance prediction of corroding concrete bridges with field monitoring
ABSTRACT: Continuous monitoring of critical aging bridges has become necessary due to increased traffic loads, changing environments, extreme shocks, which can reduce their load-bearing capacities, modify their failure modes, and increase their risks of failure. Implementation of monitoring programs can provide valuable information on physical health of bridges and their risks of failure. Prediction models updated with monitoring data can help decision makers optimize inspection, maintenance, and rehabilitation of bridges, thus extending their service life and reducing their life-cycle costs. This paper provides an approach based on the monitoring of life cycle performance of concrete bridges exposed to chlorides, and demonstrates its application in a case study. It is first shown that some of the data, which are commonly used by engineers as input values into service life prediction models, can be different from actual field values, because these parameters vary widely in space and time. It is then demonstrated that service life predictions can be improved by updating the models with field monitoring data.