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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

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.

ORNL researchers used geotagged photos to map crude oil train routes in the U.S. The mapping gives transportation planners insight into understanding potential impacts along the routes. Credit: ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers used images from a photo-sharing website to identify crude oil train routes across the nation to provide data that could help transportation planners better understand regional impacts.

CFM’s RISE open fan engine architecture. Image: GE Aerospace

To support the development of a revolutionary new open fan engine architecture for the future of flight, GE Aerospace has run simulations using the world’s fastest supercomputer capable of crunching data in excess of exascale speed, or more than a quintillion calculations per second.

ORNL seismic researcher Chengping Chai placed seismic sensors on the ground at various distances from an ORNL nuclear reactor to learn whether they could detect its operating state. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Like most scientists, Chengping Chai is not content with the surface of things: He wants to probe beyond to learn what’s really going on. But in his case, he is literally building a map of the world beneath, using seismic and acoustic data that reveal when and where the earth moves.

Data Center World keynote presenter, Bill Kleyman, right, presented ORNL’s Paul Abston with the Data Center Manager of the Year 2023 award during the conference’s general session on May 9. Credit: Data Center World AFCOM

Paul Abston, leader of the HPC Infrastructure Operations Group of the National Center for Computational Sciences and manager of the Oak Ridge Leadership Computing Facility’s data center, has been named Data Center Manager of the Year for 2023.

ORNL researchers used diamonds to compress materials to 1.2 million times ambient pressure and software to remove signal interference and extract data on pressure-induced atomic structures. Credit: Jill Hemman/ORNL, U.S. Dept. of Energy

For decades, scientists sought a way to apply the outstanding analytical capabilities of neutrons to materials under pressures approaching those surrounding the Earth’s core.

ORNL researchers encoded grid hardware operating data into a color band hidden inside photographs, video or artwork, as shown in this photo. The visual can then be transmitted to a utility’s control center for decoding. Credit: ORNL/U.S. Dept. of Energy

Inspired by one of the mysteries of human perception, an ORNL researcher invented a new way to hide sensitive electric grid information from cyberattack: within a constantly changing color palette.

Climate change often comes down to how it affects water, whether it’s for drinking, electricity generation, or how flooding affects people and infrastructure. To better understand these impacts, ORNL water resources engineer Sudershan Gangrade is integrating knowledge ranging from large-scale climate projections to local meteorology and hydrology and using high-performance computing to create a holistic view of the future.

Climate change often comes down to how it affects water, whether it’s for drinking, electricity generation, or how flooding affects people and infrastructure. To better understand these impacts, ORNL water resources engineer Sudershan Gangrade is integrating knowledge ranging from large-scale climate projections to local meteorology and hydrology and using high-performance computing to create a holistic view of the future.

An AI-generated image representing atoms and artificial neural networks. Credit: Maxim Ziatdinov, ORNL

Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.