Deterioration Modeling of Concrete Bridges and Potential Nanotechnology Application

Abstract

AbstractManagement of aging concrete bridges with limited resources can be a challenge for state authorities. Deterioration modeling of concrete bridges at the component level is essential to optimize maintenance actions and ensure the safety and serviceability of the bridge network. In this study we examined the Level 2 visual inspection data of a concrete bridge’s components collected over 4–5 inspection cycles with the objective of predicting deterioration of components and the bridge’s life cycle. With the increasing application of nanotechnology to increase the mechanical properties and durability of concrete material for bridge structures, the deterioration of nano-based concrete could be significantly different from conventional concrete. A range of deterioration prediction methods, including deterministic models and stochastic models, were examined to understand the validity of the different methods in predicting the deterioration of bridge components made of conventional and nano-based materials. A case study with a demonstration on a concrete open girder was investigated with regard to linear regression models and the stochastic Markov deterioration model. The outcomes can be used to support future study on the performance of conventional and nano-based concrete materials and their lifecycles in the asset management of bridges.