Description

Corrosion of buried steel, a critical component of American transportation infrastructure, remains one of the most insidious challenges due to the uncertainty associated with its estimates. Predicting when and how this corrosion happens is very difficult. This uncertainty grows exponentially with time, making corrosion estimation in the long term even more challenging, especially with buried steel and steel structures, which cannot even be monitored visually. While significant advancement has been made to understand the effect of the various corrosion parameters on soil corrosivity, there is a lack of a comprehensive understanding of how these factors collectively contribute to corrosion as they vary simultaneously and continuously with time. This project evaluates soil resistivity and corrosivity in controlled, constant conditions, considering the various key parameters that contribute to corrosion of buried steel. The project involved devising a new experimental protocol, developing and implementing a comprehensive experimental program by varying one testing parameter at a time. The results of the testing program showed the potential of the experimental approach to provide the necessary data to develop empirical prediction models for soil resistivity. Additionally, a new experimental method was piloted for this project to capture the variation in soil resistivity in a continuously varying environment. Finally, the researchers compiled a large digital database of real-world corrosion measurements and site information. Using advanced data analysis techniques, they created a model that can help predict corrosion in buried steel structures and estimate the level of uncertainty in those predictions. Better predictions of corrosion can help engineers and infrastructure managers identify risks earlier, plan maintenance more effectively, and extend the life of critical infrastructure such as pipelines, bridges, and transportation systems, therefore helping to reduce costly failures, improve safety, and support more reliable systems.

Publication Date

5-5-2026

Publication Type

Report

Topic

Miscellaneous, Transportation Engineering

Digital Object Identifier

10.31979/mti.2026.2523

MTI Project

2523

Keywords

Deterioration, Corrosion, Wear, Aging, Asset management

Disciplines

Civil Engineering | Construction Engineering and Management

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