TWEET ARCHIVE CRACK

“Without an autonomous and objective process for assessing damage to the many reinforced concrete structures that make up our built environment, these tragic structural failures are sure to continue,” Ebrahimkhanlou said.

TWEET ARCHIVE CRACK

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. 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. But inspections are time-consuming, and often inconsistent, processes, heavily dependent on the judgment of inspectors. Iowa, have centered the need for more frequent and thorough inspections of aging buildings and infrastructure across the country. Recent structural collapses, including tragedies in Surfside, Florida, Pittsburgh, New York City and Davenport.

College of Engineering researchers have developed a method for quickly assessing damage to reinforce concrete structures by using artificial intelligence algorithms to identify patterns in their surface cracking.

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