Probabilistic evaluation method for corrosion risk of steel reinforcement based on concrete resistivity

In order to overcome the disadvantages of traditional deterministic methods, a probabilistic evaluation method to assess the corrosion risk of steel reinforcement in concrete was proposed based on the probabilistic prediction model of concrete resistivity. The influences of major influential factors including water-to-cement ratio, chloride content, ambient temperature and ambient relative humidity on concrete resistivity were investigated first. Then a probabilistic prediction model of concrete resistivity in terms of the above major influential factors was developed by using the Bayesian theory and the Markov Chain Monte Carlo (MCMC) method. Meanwhile, the evaluation criterion for corrosion risk of steel reinforcement based on concrete resistivity was proposed according to the relationship between concrete resistivity and corrosion rate of steel reinforcement. Finally, a probabilistic evaluation method for corrosion risk of steel reinforcement in concrete was developed by means of the proposed probabilistic prediction model of concrete resistivity. Analysis results show that the proposed probabilistic evaluation method can not only identify the dominant risk of reinforcement corrosion, but also determine the probabilities of steel reinforcement under different corrosion risk levels (e.g. negligible, low, moderate, and high), which could avoid the misjudgment of corrosion risk of steel reinforcement often encountered by the traditional deterministic evaluation methods.