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July 28, 2021

Ground Shaking AI!

NSF-funded researchers use AI to improve disaster resilience, protect human life and minimize damage and economic losses during earthquakes.

Credit: National Science Foundation


Ground-shaking AI!

Hi, I'm Mo Barrow with The Discovery Files, from NSF -- the U.S. National Science Foundation.

Imagine, you're taking a leisurely stroll and you hear something like this in the distance. Then, the ground beneath your feet begins to shake violently, moving several feet.

On February 22, 2011, the people of Christchurch, New Zealand knew that experience well. They endured a magnitude 6.3 earthquake.

The event provided a unique laboratory for researchers from The University of Texas at Austin, funded by the NSF.

A major feature of the Christchurch earthquake was liquefaction -- when extreme shaking of solid ground causes water pressure to rise -- turning earth into liquid. The researchers developed a type of artificial intelligence known as machine learning -- a computer model used to predict the amount of lateral movement during the quake due to liquefaction.

They trained the model using displacements from 7,000 points and then used the model to predict displacements at 2.5 million additional points around the quake's epicenter -- predicting liquefaction with some 80% accuracy and earth displacement with 70% accuracy.

Using the NSF-supported Texas Advanced Computing Center's Frontera Supercomputer, in partnership with the design-safe cyberinfrastructure -- part of NSF's natural hazards engineering research infrastructure, the researchers are applying AI to improve disaster resilience, protect human life and minimize damage and economic losses during natural hazard events -- helping to keep your feet on solid ground.

Discover how the U.S. National Science Foundation is advancing research at nsf.gov.

"The discovery files" covers projects funded by the government's National Science Foundation. Federally sponsored research -- brought to you, by you! Learn more at nsf.gov or on our podcast.


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