A new computational model developed by researchers at MIT takes ambient vibrations and analyzes them to pick out features in the noise to give indications of a building’s stability, MIT News reports. The feedback can then be used to monitor the building for damage or mechanical stress. Think of it as getting your blood pressure or cholesterol checked regularly to find warning signs of future problems before they become too dire.
The model is being tested on the tallest building on the MIT campus, the 21-story Green Building, a research building made of reinforced concrete. The researchers attached 36 accelerometers to selected floors from the building’s foundation to its roof to record vibrations.
But in order for these recordings to actually serve a purpose, the team needed to figure out how to take the data and link it to the health characteristics of the building, according to Oral Buyukozturk, a professor in MIT’s Department of Civil and Environmental Engineering.
Their solution was to create a computer simulation of the Green Building as a finite element model. MIT News describes this type of model as “a numerical simulation that represents a large physical structure, and all its underlying physics, as a collection of smaller, simpler subdivisions.” The researchers then added parameters to the model, such as the strength and density of concrete walls, slabs, beams, and stairs in each floor.
With all of this done, the researchers are able to then add something like the vibration caused by a passing truck to the simulation in order to see how the model predicts the building and its elements would respond. To make the model as accurate as possible, data from the Green Building's accelerometers was mined and analyzed for key features relating to the building’s stiffness and other indicators of health.
The more data that is added over time, the more intelligent the system becomes. The researchers say they are confident that any real life damage in the building will show up in the system.
This type of model will be especially useful to immediately see, after an event such as an earthquake, if and where there is damage to the building.
The researchers’ vision is for a system such as this to be outfitted on all tall buildings, making them intelligent enough to monitor their own health and provide increased resiliency.
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