Methodology of a predictive tool for corrosion prediction and risk- based maintenance in reinforced concrete structures

This paper contributes to the understanding and prediction of the corrosion condition of steel in reinforced concrete structures while proposing solutions to reduce both financial and ecological costs associated with their maintenance. It presents a comprehensive tool and methodology for predicting maintenance and repair in maritime structures and bridges that are exposed to carbonation and chloride ingress. The tool incorporates various resources, including numerical and analytic models, as well as an experimental results database based on existing literature. This database facilitates the conversion of composition parameters into input parameters for the durability models. The application of this tool is demonstrated on a maritime structure in this paper. Deterministic and probabilistic predictions using the Monte Carlo method are utilized to determine the optimal time for inspection and maintenance operations.