By Peter Murphy
Published October 14, 2021
Seyedomid Sajedi, a PhD candidate specializing in autonomous structural inspections and health monitoring, won the $8,000 O.H. Ammann Research Fellowship in Structural Engineering from the American Society of Civil Engineers (ASCE).
“Our main goal is to develop frameworks that can identify the location and severity of structural damage from different sources of information, such as images and vibration records in a timely manner,” says Sajedi, who is advised by assistant professor Xiao Liang.
Sajedi and Liang plan to use the funds to bring back a quarter-scale 39-foot steel truss bridge, originally built on UB’s campus in 2006. Researchers tested the bridge on the Structural Engineering and Earthquake Simulation Lab’s shake tables, but Sajedi will place the bridge outdoors to conduct research for structural health monitoring.
“The fact that this is an outdoor experimental setup is very exciting to me, and I look forward to the experience despite all the challenges, especially in the Buffalo winter,” Sajedi says. “These experiments help validate several aspects of our artificial intelligence (AI)-equipped health monitoring systems on a relatively large-scale structure.”
According to ASCE’s 2021 Infrastructure Report Card, 42% of the United States’ bridges are over 50-years old and over 7 of them are in “poor” condition. The machine learning models Sajedi hopes to develop can provide decision-makers with valuable information regarding repair, maintenance and safety assessment of infrastructure, and potentially save them millions of dollars.
“Structural health monitoring, especially vibration-based damage diagnosis, is one of the areas where deep learning models can be very effective,” Sajedi says.
Sajedi will utilize AI to take advantage of additional capabilities and limit the number of resources needed to address the health of different structures.
“Human inspections can be subjective and require a significant amount of resources considering a large number of infrastructure across the nation,” Sajedi says. “Deep learning, from artificial intelligence, can be a very powerful tool in the hands of engineers to perform autonomous structural health monitoring, and provides valuable insights on the location and extent of structural damage in near real-time.”
The O.H. Amman Research Fellowship helps encourage the creation of new knowledge in structural design and construction. According to Liang, this achievement will provide Sajedi with significant research flexibility.
“We are leveraging AI, the internet of thing, with other emerging technologies,” Liang says. “We hope this large-scale outdoor testbed will enhance the research capacity of the Department in smart monitoring for future bridge engineering.”