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2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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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.
Kyoung O. Lee, Robin P. Gardner
Nuclear Science and Engineering | Volume 174 | Number 3 | July 2013 | Pages 264-285
Technical Paper | doi.org/10.13182/NSE12-23
Articles are hosted by Taylor and Francis Online.
Pebble motions in pebble-bed reactors (PBRs) have been investigated by generating pebble motion histories with Monte Carlo molecular dynamics simulations. This extension of molecular dynamics to PBR-sized pebble motion is accomplished by splitting the simulation into two parts. The first part simulates the dropping of pebbles into the PBR with a closed exit that allows one to obtain the correct initial placement of all pebbles within the pebble bed. The second part simulates what happens when the PBR exit is opened and normal pebble flow begins. Using this combined approach the pebble piling up and subsequent discharge are predicted. Simulations have been conducted with this approach by monitoring the mass flow rate, the pebble piling up, and the subsequent discharge for a range of pertinent parameters using the Hertz-Mindlin force for pebble interactions. The simulation output data include the force, velocity, and position of the pebbles as a function of time. Note that arching or locked flow, a very important phenomenon, is predicted by this approach under certain operating conditions. Using this approach, PBR results (including arching) for a range of the parameters of interest are reported and are discussed herein.