Multi-NDE Technology Approach to Improve Interpretation of Corrosion in Concrete Bridge Decks Based on Electrical Resistivity Measurements

This research aimed to improve the interpretation of electrical resistivity (ER) results in concrete bridge decks by utilizing machine-learning algorithms developed using data from multiple nondestructive evaluation (NDE) techniques. To achieve this, a parametric study was first conducted numerical simulations investigate effect various parameters on ER measurements, such as degree saturation, corrosion length, delamination depth, cover, and moisture condition delamination. A set this used build algorithm based Random Forest methodology. Subsequently, applied collected an actual deck BEAST® facility, showcasing significant advancement measurement through incorporation information other NDE technologies. Such strides are pivotal advancing reliability assessments structural elements for their durability safety.