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Published in the style of MaxQ Magazine | Fall 2024 Issue

– On a humid morning in July, a 60-year-old concrete overpass on I-35 did something no one expected: it whispered.

Not with sound, but with data. A hairline fracture, invisible to the human eye, had expanded by 0.4 millimeters during a heatwave. Within 30 seconds, an AI model at the Oden Institute for Computational Engineering and Sciences flagged the anomaly, sent a text alert to TxDOT, and calculated the exact tonnage of weight the joint could still bear. maxq magazine pdf

"We caught a bearing lock in El Paso three months before it would have seized during a winter freeze," recalls Marco Diaz (B.S. '20), the project's lead field engineer. "The bridge didn't look broken. It felt broken to the AI. We replaced a $400 part instead of rebuilding a $4 million span." However, the project raises a provocative question: If a bridge can tell you it is dying, who is liable if you ignore it?

This is not science fiction. This is the new frontier of "Sentient Infrastructure." Led by Dr. Priya Varma (Ph.D. '12), a team of civil and aerospace engineers has successfully retrofitted three major Texas bridges with a network of fiber-optic sensors and machine learning algorithms. Dubbed the "Bone & Steel Project," the system mimics the human nervous system. Published in the style of MaxQ Magazine |

How UT Engineers are teaching bridges, dams, and pipelines to "feel" pain before they break.

"We want infrastructure to have a voice," says Varma, leaning over a holographic projection of the Pennybacker Bridge. "We just need to be brave enough to listen." Within 30 seconds, an AI model at the

"Bones don't break without a warning crack," says Varma, who holds the Temple Foundation Chair in Smart Materials. "Steel doesn't snap without yielding. Our problem isn't a lack of data; it's a lack of translation. We built a translator."