Updating Durability Models for Concrete Structures in Chlorine Environment Based on Detection Information

Abstract

The assessment of concrete structure durability in chlorine environments is significantly impacted by the uncertainty inherent in existing durability models. It introduces an integrated approach for updating these models based on the detection information of existing structures. This approach narrows the gap between theoretical predictions and observed structural durability. Specifically, we refined the probability model of critical chloride content by analyzing steel bar corrosion sample proportions using Bayesian theory for greater accuracy. The enhanced model enables more reliable life expectancy prediction, forming a solid foundation for maintaining and strengthening existing structures. This method was demonstrated through a case study of a reinforced concrete industrial building with a service life of 12 years.