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2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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Latest News
AI at work: Southern Nuclear’s adoption of Copilot agents drives fleet forward
Southern Nuclear is leading the charge in artificial intelligence integration, with employee-developed applications driving efficiencies in maintenance, operations, safety, and performance.
The tools span all roles within the company, with thousands of documented uses throughout the fleet, including improved maintenance efficiency, risk awareness in maintenance activities, and better-informed decision-making. The data-intensive process of preparing for and executing maintenance operations is streamlined by leveraging AI to put the right information at the fingertips for maintenance leaders, planners, schedulers, engineers, and technicians.
T. Craciunescu, A. Murari, I. Tiseanu, J. Vega, JET-EFDA Contributors
Fusion Science and Technology | Volume 62 | Number 2 | October 2012 | Pages 339-346
Selected Paper from the Seventh Fusion Data Validation Workshop 2012 (Part 1) | doi.org/10.13182/FST12-A14625
Articles are hosted by Taylor and Francis Online.
Multifaceted asymmetric radiation from the edge (MARFE) instabilities may reduce confinement leading to harmful disruptions. They cause a significant increase in impurity radiation, and therefore, they leave a clear signature in the video data. This information can be exploited for automatic identification and tracking. A MARFE classifier, based on the phase congruency theory, has been developed and adjusted to extract the structural information in the images of Joint European Torus (JET) cameras. This approach has the advantage of using a dimensionless quantity and providing information that is invariant to image illumination, contrast, and magnification. The method was tested on JET experimental data and has proved to provide a good prediction rate.