We present a novel, fundamentally sound approach for the determination of corrosion rate and anode location in reinforced concrete. In this contribution, we focus on the sensitivity of this non-destructive method with respect to the state of corrosion and concrete properties. Corrosion is often the main cause for the premature deterioration of reinforced concrete structures. Especially the type of pitting (or localized) corrosion poses great danger, as it can result in fast local decrease of the steel diameter. Non-destructive testing (NDT) is essential to detect the corrosion at an early stage, without the need to damage the concrete. The most commonly applied NDT method for reinforced concrete is potential mapping. However, it only predicts the probability of corrosion at a certain location, and does not supply any information about the corrosion rate. Other electrochemical measurements targeting corrosion rate rely on the polarization resistance, based on the mixed-potential theory by Wagner and Traud [1938]. This theory, however, is not applicable to localized corrosion. A novel inverse modelling approach allows us to detect and quantify corrosion, based on electrical potential measurements at the concrete surface in combination with a small perturbation of the corroding system by an external electrode. Using a 3D finite-element model to describe the electrical potential field resulting from external polarization of the corroding steel, we estimate the location and rate of corrosion through the application of inverse methods. This study presents the sensitivity of the approach with respect to the degree of corrosion and the concrete properties themselves. We investigated effects of the width of the corroding spot, the cover thickness and the concrete resistivity. First, we analyzed the direct effect of the potentials measured at the surface, using the finite-element model. Secondly, we determine the range of these factors for which the inverse method is able to accurately estimate the corrosion rate and location. This information allows us to understand the limitations of inverse modelling of electrical potential in detecting corrosion in reinforced concrete.
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