Refined half-cell potential mapping for corrosion detection using inverse modeling

Abstract

Accurate determination of the locations and sizes of actively corroding areas on embedded steel reinforcement in concrete is rather challenging using the standardized half-cell potential mapping technique. In this research, it is hypothesized that half-cell potentials on the surface of the concrete can be used, beyond their originally intended purpose, to identify the locations and sizes of anodic and cathodic sites on the steel reinforcement by means of inverse modeling algorithms. The problem, simply put, is a boundary identification problem: given the potential measurements on the surface of the concrete, identify the anodic and cathodic boundaries on the surface of the reinforcement. To this end, a conjugate-gradient based inverse modeling algorithm is developed to assimilate standard half-cell potential measurements on the concrete surface and to calculate the potential distribution on the surface of the reinforcement. The performance of the inverse model is demonstrated with various configurations of corroding systems with single and multiple anodes using identical twin numerical experiments. The results show that the developed inverse modeling algorithm is robust and can be used as a starting point to investigate more practical cases for which the number of observation points on the surface of the concrete is limited.