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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.
Jing Wang, Ronald G. Ballinger, Heather J. Maclean
Nuclear Technology | Volume 148 | Number 1 | October 2004 | Pages 68-96
Technical Paper | Materials for Nuclear Systems | doi.org/10.13182/NT04-A3549
Articles are hosted by Taylor and Francis Online.
An integrated fuel performance model for coated particle fuel has been developed to comprehensively study the behavior of TRISO-coated fuel. Modeling of both pebble-bed and prismatic configurations is possible. In the case of the pebble-bed concept, refueling of pebbles is simulated to account for the nonuniform environment in the reactor core and history-dependent particle behavior. Monte Carlo sampling of particles is employed in fuel failure prediction to capture the statistical features of dimensions; material properties; and, in the case of the pebble-bed concept, the statistical nature of the refueling process. An advanced fuel failure model has been developed based on a probabilistic fracture mechanics approach. The mechanical analysis includes effects of anisotropic irradiation-induced dimensional changes and isotropic irradiation-induced creep, and the fluence-dependent Poisson ratio in irradiation creep. The stress analysis is benchmarked against the calculations of Japanese High Temperature Test Reactor (HTTR) first-loading fuel and finite element result on one case performed by the Idaho National Engineering and Environmental Laboratory. The failure model predictions are compared with NPR1, NPR2, and NPR1A capsule irradiation data. The model results compare very favorably with postirradiation examination results both in terms of failure probability, number of failed particles, and Kr85m R/B evolution during irradiation.