This work seeks to present a systematic study that aimed to provide quantitative understanding of the fundamental factors that influence the chloride threshold of pitting corrosion of steel in concrete, by conducting a set of laboratory tests to assess the corrosion potential (Ecorr) and pitting potential (Epit) of steel coupons in simulated concrete pore solutions.
With the aid of artificial neural network, the laboratory data were used to establish a phenomenological model correlating the influential factors (total chloride concentration, chloride binding, solution pH, and dissolved oxygen (DO) concentration) with the pitting risk (characterized by Ecorr−Epit). Three‐dimensional response surfaces were then constructed to illustrate such predicted correlations and to shed light on the complex interactions between various influential factors.
The results indicate that the threshold [Cl−]/[OH−] of steel rebar in simulated concrete pore solutions is a function of DO concentration, pH and chloride binding, instead of a unique value.
The limitations and implications of the research findings were also discussed.
This research could have significant practical implications in predicting the service life of new or existing reinforced concrete in chloride‐laden environments.
This study further advances the knowledge base relevant to the chloride‐induced corrosion of steel rebar in concrete.
Shi, X., Anh Nguyen, T., Kumar, P. and Liu, Y. (2011), "A phenomenological model for the chloride threshold of pitting corrosion of steel in simulated concrete pore solutions", Anti-Corrosion Methods and Materials, Vol. 58 No. 4, pp. 179-189. https://doi.org/10.1108/00035591111148894
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