Predictive and Diagnostic Load Rating Model of a Prestressed Concrete Bridge

Abstract

This paper presents a probabilistic model of the load rating process incorporated with field inspection observations applied to a prestressed concrete bridge to capture deterioration characteristics. The main computational tool used is a Bayesian network. The model is developed around the main load-carrying member, an interior beam, and the effects of corrosion of its interior steel. Bridge load ratings are calculated as variables based on the following design methodologies: allowable stress; load factor; and load and resistance factor design. Two investigations on an actual bridge are conducted that demonstrate the predictive and diagnostic capabilities of the model. The results show the usefulness of this model in bridge management.