Project Summary

The proposed research merges a materials science and engineering approach to corrosion science with structural engineering approaches to bridge inspection and assessment to generate and implement a corrosion prediction model for bridge inspection and asset management systems. We build on prior work identifying the progression of corrosion as a function of local chloride ion concentration ([Cl-]). The proposed work includes lab-based objectives that establish thresholds of local [Cl-] for corrosion formation and impacts of galvanic coupling, sandblast cleaning, and Znbased coating systems on corrosion rates. Through accelerated corrosion testing, polarization testing, and characterization of samples, a corrosion prediction model will be built for field-use. Field-based objectives include comparison of lab-based data to field collected samples and the validation of the prediction model with data gathered through bridge inspections. By working closely with two CTDOT technical contacts, we will refine and implement the prediction model on a selection of pilot bridges in the field. Regular meetings with DOT contacts as well as the creation of an education and implementation program for the use of the refined model are key aspects of the technology transfer of the proposed research. This approach is modeled after a successful project with CTDOT in which a novel 3D scanning inspection methodology was researched, piloted, and ultimately adopted by CTDOT. The proposed work is highly relevant to New England bridges where chlorine exposure from water and de-icing salts are common.