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.