Artificial Intelligence Can Identify Patterns in Surface Cracking to Assess Damage in Reinforced Concrete Structures

Cracks in a concrete structure

Recent structural collapses, including tragedies in Surfside, Florida , Pittsburgh , New York City and Davenport. Iowa , have centered the need for more frequent and thorough inspections of aging buildings and infrastructure across the country. But inspections are time-consuming, and often inconsistent, processes, heavily dependent on the judgment of inspectors. Researchers at Drexel University and the State University of New York at Buffalo are trying to make the process more efficient and definitive by using artificial intelligence, combined with a classic mathematical method for quantifying web-like networks, to determine how damaged a concrete structure is, based solely on its pattern of cracking.

In the paper “A graph-based method for quantifying crack patterns on reinforced concrete shear walls,” which was recently published in the journal Computer-Aided Civil and Infrastructure Engineering, the researchers, led by Arvin Ebrahimkhanlou, PhD , an assistant professor in Drexel’s College of Engineering , and Pedram Bazrafshan, a doctoral student in the College, present a process that could help the country better understand how many of its hundreds of thousands of aging bridges, levees, roadways and buildings are in urgent need of repair.

Read more in the Drexel newsroom.