A substantial part of corrosion research relies on the analysis of polarization curves to obtain corrosion currents, Tafel slopes and other parameters, such as exchange current densities. This, often manual analysis remains highly subjective, which hampers the reproducibility of corrosion research and makes comparison of reported Tafel slopes, corrosion rates, or exchange current densities from different literature sources difficult. One reason is that the analysis is strongly influenced by the selected range of the measured data. To improve this, we developed a Python library for the reliable analysis of polarization curves. A particular novelty is an algorithm designed to fit polarization curves under mixed activation-diffusion control, which is a situation often encountered in corrosion research. This algorithm reduces the subjectivity related to the measured or selected potential range. Moreover, the algorithm offers the possibility to diagnose and quantify the accuracy of the fit. We use experimentally measured polarization curves to test the proposed approach, and show that for curves without a clear, purely activation controlled Tafel region in the cathodic branch, accurate and consistent analysis is only possible by applying the mixed activation-diffusion control technique. Re-evaluation of literature data shows that by applying the library, the variability in reported Tafel slopes can be greatly reduced. Thus, the here proposed approach and the related open access Python library for the analysis of polarization curves may foster reproducibility and enhance comparability of data measured in corrosion research.
We present an approach, termed electrochemical tomography (ECT), for the in-situ study of corrosion phenomena in general, and for the quantification of the instantaneous rate of localized corrosion in particular. Traditional electrochemical techniques have limited accuracy in determining the corrosion rate when applied to localized corrosion, especially for metals embedded in opaque, porous media. One major limitation is the generally unknown anodic surface area. ECT overcomes these limitations by combining a numerical forward model, describing the electrical potential field in the porous medium, with electrochemical measurements taken at the surface, and using a stochastic inverse method to determine the corrosion rate, and the location and size of the anodic site. Additionally, ECT yields insight into parameters such as the exchange current densities, and it enables the quantification of the uncertainty of the obtained solution. We illustrate the application of ECT for the example of localized corrosion of steel in concrete.
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.
The densely populated Po Plain, a very deep sedimentary basin in northern Italy, is prone to heavy shaking during earthquakes. Seismic hazard assessment must account for local variation in wave amplification. Standard ground motion prediction equations may fail to picture the complexity of strong lateral gradients in seismic response, due to sharp structural heterogeneity. For this reason, there is an increasing demand for full waveform predictions for engineering applications. Here, we present an implementation of a hybrid broadband simulation based on the method of Mai et al. (Bull Seismol Soc Am 100(6):3338-3339, 2010), to obtain complete broadband seismograms of 0.1-10 Hz. With this method, low frequency (\ 1 Hz) and high frequency (1-10 Hz) seismograms are simulated separately using a deterministic and a stochastic method, respectively. We apply the method to four events recorded within the Po basin, with magnitude ranging from Mw = 4.4 to Mw = 5.6. The low frequency (LF) simulation is performed using SPECFEM3D on a few test subsurface velocity models. The three-dimensional velocity model MAMBo (Molinari et al. in Bull Seismol Soc Am 105(2A):753-764, 2015)-consisting of a detailed structural description of the basin, based on extensive active-source data, embedded within a regional 3D crustal model-provided the best results for broadband simulations that most closely corresponded with the observations. It performed better than an ambient noise tomography model with more accurate S-wave velocities but less well defined layer topographies, emphasizing the importance of first order velocity discontinuities. The high frequency (HF) seismograms are simulated using the multiple scattering approach of Zeng et al. (J Geophys Res Solid Earth 96(B1):607-619, 1991). The scattering coefficients are obtained by performing a non linear inversion for each station to find best fitting synthetic envelopes. HF energy is then combined at $ 1 Hz to match the amplitude and phase spectra of the LF signal. We are able to simulate full waveforms throughout the Po Plain, of which shaking duration matches observed data for stations located in the basin. Shaking amplitudes are generally overestimated in the low frequency simulation by the MAMBo velocity model. Updating the MAMBo velocity model with more accurate S-wave velocity information of the ambient noise tomography model should improve the fit in future simulations.
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