"The broader implication is, after an event like an earthquake, we would see immediately the changes of these features, and if and where there is damage in the system," said Oral Buyukozturk, a professor at MIT.
"This provides continuous monitoring and a database that would be like a health book for the building, as a function of time, much like a person's changing blood pressure with age," said Buyukozturk.
The team tested its computational model on a 21-story building made in the 1960s using reinforced concrete.
"These sensors represent an embedded nervous system," Buyukozturk said.
The team first built a computer simulation of the building that represents physical structure, and all its underlying physics.
They then plugged various parameters into the model, including the strength and density of concrete walls, slabs, beams, and stairs in each floor.
As the model is designed, researchers should be able to introduce an excitation in the simulation - for example, a truck-like vibration - and the model would predict how the building and its various elements should respond.
"So we are updating the model with actual measurements to be able to give better information about what may have happened to the building," he said.
To more accurately predict a buildin's response to ambient vibrations, the group mined data from the building's accelerometers, looking for key features that correspond directly to a building's stiffness or other indicators of health.
They developed a new method with the seismic interferometry concept that describes how a vibration's pattern changes as it travels from the ground level to the roof.
"Outfitted with sensors and central processing algorithms, those buildings will become intelligent, and will feel their own health in real time and possibly be resilient to extreme events," said lead author Hao Sun.
The study was published in the journal Mechanical Systems and Signal Processing.
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