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ORNL researchers are establishing a digital thread of data, algorithms and workflows to produce a continuously updated model of earth systems.

Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.

 

Director of ORNL’s AI Initiative Prasanna Balaprakash addresses attendees at the Generative AI for ORNL Science Workshop. Credit: ORNL, U.S. Dept. of Energy

The Department of Energy’s Oak Ridge National Laboratory hosted its Smoky Mountains Computational Science and Engineering Conference for the first time in person since the COVID pandemic broke in 2020. The conference, which celebrated its 20th consecutive year, took place at the Crowne Plaza Hotel in downtown Knoxville, Tenn., in late August.

Cody Lloyd stands in front of images of historical nuclear field testing. The green and red dots are the machine learning algorithm recognizing features in the image. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Cody Lloyd became a nuclear engineer because of his interest in the Manhattan Project, the United States’ mission to advance nuclear science to end World War II. As a research associate in nuclear forensics at ORNL, Lloyd now teaches computers to interpret data from imagery of nuclear weapons tests from the 1950s and early 1960s, bringing his childhood fascination into his career

Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

After completing a bachelor’s degree in biology, Toya Beiswenger didn’t intend to go into forensics. But almost two decades later, the nuclear security scientist at ORNL has found a way to appreciate the art of nuclear forensics.

Two researchers standing back to back in a grassy area

When geoinformatics engineering researchers at the Department of Energy’s Oak Ridge National Laboratory wanted to better understand changes in land areas and points of interest around the world, they turned to the locals — their data, at least.

Tristen Mullins. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Tristen Mullins enjoys the hidden side of computers. As a signals processing engineer for ORNL, she tries to uncover information hidden in components used on the nation’s power grid — information that may be susceptible to cyberattacks.

Heat impact map

A detailed study by Oak Ridge National Laboratory estimated how much more—or less—energy United States residents might consume by 2050 relative to predicted shifts in seasonal weather patterns 

ORNL staff members (from left) Ashley Shields, Michael Galloway, Ketan Maheshwari and Andrew Miskowiec are collaborating on a project focused on predicting and analyzing crystal structures of new uranium oxide phases. Credit: Jason Richards/ORNL

Scientists at the Department of Energy’s Oak Ridge National Laboratory are working to understand both the complex nature of uranium and the various oxide forms it can take during processing steps that might occur throughout the nuclear fuel cycle.

As part of a preliminary study, ORNL scientists used critical location data collected from Twitter to map the location of certain power outages across the United States.

Gleaning valuable data from social platforms such as Twitter—particularly to map out critical location information during emergencies— has become more effective and efficient thanks to Oak Ridge National Laboratory.