Led by Piervincenzo (Piero) Rizzo, associate professor of civil and environmental engineering, the researchers compared model data to field data gathered from three similar concrete box bridges with existing wireless sensors. The team compared those field results against finite element models, which simulate various loading or impact conditions, including the vibrations, displacement, and deformation a truck creates.
“The scope of studies like this one is to understand how a specific structure responds to traffic load to wind loads, or to other manmade or natural events,” said Rizzo.
Funding for such studies is important to meet the increasing interest in bridge monitoring, he added. The Federal government mandates that every bridge is inspected at least once every two years. Tracking issues such as corrosion, concrete spalling, or cracking may provide advance warning of potential issues between physical inspections.
Bridges expand or contract when the temperature increases or decreases. Monitoring over a one- or two-year period, during all four seasons, provides a clearer picture on the uniformity of expansion or contraction, and insight into the safety of the structure and operation of the bridge, Rizzo said.
“There are different ways of how we can monitor and inspect structures,” he continued. “To some extent, it's like tools and instruments to detect and monitor the health of a person,” similar to how different tests such as bloodwork or ultrasounds can help diagnose different human health issues.
“You cannot go there and start cutting parts and see how the damaged bridge would respond when a truck crosses across the bridge,” Rizzo said of the challenges to bridge monitoring. “We use computer models to simulate the different scenarios and how [they] would be translated into the real world,” he added.
Looking at a specific load of a truck including all relevant data of its design and its weight, the team calculated mathematical models and compared those predictions with the experimental values obtained by the existing sensors already placed on the three concrete box bridges. Rizzo’s team had no input on the type or placement of these already existing sensors.
The results showed that finite element models along with the data-driven methodologies have the potential to identify damages and anomalies in the three box girder bridges with relative accuracy. The results verified expectations, minus one or two non-consequential outliers.
Cross section of (from top) Somerset Bridge, Cooks Mill Bridge, and Tonolaway Creek Bridge, with locations of sensors shown in red. Image: Rizzo, et al.
A peer review process in 2020 resulted in Rizzo’s team finding about 70 bridges in the U.S. that already had some sort of monitoring devices on them. While he doesn’t have additional data to say for sure, he thinks there are many more sensors already applied to bridges.
“I am 99.9 percent sure that there are more than 70 bridges that have been monitored at some time in their lifespan,” said Rizzo. Those potential additional bridges may provide additional valuable field data to advance future efforts in wireless sensor monitoring for infrastructure.
“The very interesting thing is that these mathematical models that we developed could be adapted to other similar bridges—bridges that are a bit longer or a bit wider,” Rizzo said. He noted the value of such studies by academia to help provide complementary tools to the infrastructure industry. A model and remote wireless sensor approach also provides flexibility to adapt and address whatever issues may be affecting different types of bridges in different locations and conditions.
“Tell me what you need to look at and I'll tell you the best cost-effective solution,” Rizzo said.
Nancy Kristof is a technology writer in Denver.
