A new ratings system that improves damage detection and measurement could help prevent catastrophic failures of pipelines, bridges and other concrete structures, scientists say.
|"If a system like this had existed, inspectors might have foreseen there would be a problem with the Minneapolis bridge" that collapsed into the Mississippi River in 2007, one researcher said.|
Researchers at Kansas State University say their “bridge health index” more accurately describes the amount of damage in a bridge, taking subjective decisions out of the inspection process.
Similar bridge health indexes have been used in Wisconsin, California and other states over the last decade. But the Kansas scientists say theirs can also be applied to gas pipelines, dams, buildings, airplanes and other structures.
Making the Process Objective
Current methods of inspecting bridges are very subjective, said Hayder Rasheed, associate professor of civil engineering.
Equally experienced inspectors from the Federal Highway Administration in the U.S. Department of Transportation can reach different conclusions when they visually inspect bridges and determine damage amounts, the team says.
One inspector may deem a bridge 70 percent damaged; another, 80 percent.
"It varies from inspector to inspector," said Rasheed. "They measure the cracks in the bridge, but they have no objective way to calculate how much it is damaged. Because the inspectors decide which bridges are repaired first, it's very important to make the process objective across the board."
Analysis and Modeling
The bridge health index provides a more objective way to determine and compare bridge damage, to decide which bridges most need repairs, developers say.
|The I-35 Bridge failure originated with a fractured gusset plate—the kind of flaw that a more thorough damage assessment may have uncovered, researchers said.|
The engineers have developed ways to take bridge measurements and use finite element analysis and neural network modeling to back-calculate and detect damage. The network allows inspectors to input parameters, such width, depth and location of cracks in a bridge, and the network will tell the structure's health index.
A new, undamaged bridge has a health index of 100. The index goes down as the structure ages or is damaged.
"The health index is one systematic approach in a sense," said Yacoub Najjar, KSU professor of civil engineering, the team member who provided expertise in neural networks. "Inspectors gather information about the bridge, put in the information, and they receive the health index of the bridge.
“It makes it easier to study the bridge, because you bring all of these dimensions into one number. But when you have multiple dimensions, it is difficult to rate them."
Averting Another I-35 Disaster
The researchers said the health index system could lead to safer bridges and prevent the recurrence of catastrophic events like the 2007 collapse of the I-35W Mississippi River Bridge in Minneapolis.
"If a system like this had existed, inspectors might have foreseen there would be a problem with the Minneapolis bridge," Najjar said. "It might have been weak in certain areas, but other elements might have been very healthy. If you don’t have a health index to reflect that, you won't be able to rate it."
With financial support from the Kansas Department of Transportation, the team wants to develop the network model into a tool that the DOT can use.
The engineers have also discovered numerous applications of the index, saying the same modeling system can be applied to dams, buildings, airplanes and other structures.
"Using this system on airplanes is especially effective, because you deal with specific material and you can understand its behavior even better," Najjar said. "You can test the wing of an airplane and find its health index."
Thousands of Simulations
The research team has been building and training the health index system with synthetic bridges that can simulate how bridges will act under certain conditions. The network is based on thousands of simulations.
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 it can detect and predict cracks. After that work, the team will test bridges throughout the state.
"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."