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Conference Spotlight
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.
C. C. Meek, M. J. Morris, R. G Doerner, R. F. Hurt
Nuclear Science and Engineering | Volume 79 | Number 2 | October 1981 | Pages 202-211
Technical Paper | doi.org/10.13182/NSE81-A27409
Articles are hosted by Taylor and Francis Online.
A phenomenological model is developed to analyze temperature fluctuations in experiments that simulate various liquid-metal fast breeder reactor accident scenarios. Simplified mass, momentum, and energy equations are used to provide a unified system for analysis. Predictions of temperature autocovariance are compared with those observed during a representative in-pile sodium loop experiment. Good agreement is demonstrated both spatially and temporally. General results derived from the analysis of a variety of experiments are summarized and discussed with relation to reactor monitoring.