A rational data-driven probabilistic approach for assessing the condition and performance of RC structures

A variety of alternative strategies have been developed for increasing the service life of reinforced concrete structures exposed to corrosive environments. An optimum design or repair strategy requires not only an estimate of upfront costs, but also the means to compare all associated costs against the potential extension to the life of the structure. Unfortunately, however, current asset management practice, which is typically based on tacit or implicit methods for asset condition assessment, performance prediction and management is no longer enough. The objective of this research project is to develop practical life cycle deterioration models that use measured field data to assess the current condition of existing RC structures and to predict the future performance of various repair or rehab strategies on the remaining useful life of these structures. Finite element analysis, experimental and analytical programs together with a field study will be carried out to achieve the objectives of this research.

Gang Li
Faculty Supervisor: 
Mohamed Boulfiza
Partner University: