Bayesian Assessment of Corrosion Degree of Reinforced Concrete Beams Subjected to Accelerated Corrosion

Abstract

With many existing reinforced concrete structures reaching their anticipated service life, it is essential to assess their remaining capacity, particularly those affected by degradation mechanisms like corrosion. While previous studies have illustrated how to estimate corrosion levels using indirect data from static and dynamic tests, most of this research is based on simulations, often overlooking the challenges of experimental data. An experimental campaign was conducted at the Magnel-Vandepitte Laboratory of Ghent University to address this gap. Real-size reinforced concrete beams were subjected to accelerated corrosion and 4-point bending tests. The actual corrosion degree is determined by the mass loss of the reinforcement, allowing for a detailed investigation into the influence of corrosion on the measurement data. Furthermore, a Bayesian inference framework is used to estimate the corrosion degree of the beams based on the test results, providing valuable insights for practical applications.