Uncertainty-Based Model Averaging for Prediction of Corrosion Ratio of Reinforcement Embedded in Concrete

Half-cell potential (HCP) is widely acknowledged as a nondestructive method for assessing the durability of concrete, although the variability in environmental and material conditions compromises its accuracy. The reliability of traditional prediction models, which are often derived from limited data, is questionable under various conditions. This study employed a Bayesian-enhanced probabilistic model to predict corrosion reinforcement using HCP, addressing both known and unknown uncertainties. Constructed as a piecewise function, the model integrates insights from the literature with the results of an accelerated corrosion experiment conducted by the research team, thereby validating the effectiveness of the probabilistic approach. This study also examines the influence of prior knowledge on the accuracy of predictions. The findings revealed a biphasic relationship between HCP and the corroded mass reduction ratio. HCP decreased exponentially with a corroded mass reduction ratio below 15%, whereas beyond this threshold, the decline became more pronounced, modeled by a combination of exponential and cubic polynomial functions. These results underscore the critical role of employing a piecewise function to accurately define the relationship between HCP and corrosion in reinforced concrete, thereby providing a solid foundation for future durability assessments.