Kansas State University researchers Hayder Rasheed, associate professor of civil engineering, and Yacoub Najjar, professor of civil engineering, are collaborating to better detect and measure damage in concrete bridges. The researchers have created a bridge health index - a rating system that describes the amount of damage in a bridge - that can also apply to other structures, such as gas pipelines, dams, buildings, and airplanes.
Rasheed and Najjar developed ways to take bridge measurements and use finite element analysis and neural network modeling to back-calculate and detect bridge damage. They combined this process of inverse problem solving with Najjar's expertise in neural networks to create the bridge health index. Currently, the researchers and several graduate students have been building and training the health index system with synthetic bridges, which can simulate how bridges will act under certain conditions. They have built the network based on thousands of simulations.
"We take these measurements and we run them through two cycles of analysis," Rasheed said. "We come up with damage detection of where we expect the cracks to be and how deep and how wide they are. It's a very intelligent system." The next step is to build bridge beams. The engineers will create cracks in the beams and then enter measurements into their network modeling system to determine how well the system can detect and predict cracks. After working with bridge beams, the researchers will test bridges throughout the state. The researchers said the health index system could lead to safer bridges and prevent catastrophic events, like the 2007 collapse of the I-35W Mississippi River bridge in Minneapolis, from reoccurring.
