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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.
Sungwhan Cho, Jin Jiang
Nuclear Technology | Volume 161 | Number 2 | February 2008 | Pages 98-107
Technical Paper | Reactor Safety | doi.org/10.13182/NT08-A3916
Articles are hosted by Taylor and Francis Online.
A new technique for analyzing the effect of testing on shutdown system (SDS) number 1 (SDS1) in Canadian deuterium uranium (CANDU) nuclear power plants is proposed. The effect of the test on the core damage probability is quantified using a Markov process model. The model is used to derive the effect of the test frequency on the unavailability and the spurious reactor trip probability. Two core damage scenarios are considered: one from a process failure with the unavailable SDS and the other from a spurious reactor trip. The Markov process model is then used with the core damage scenarios to analyze the effect of the test frequency on the core damage probability. The quantified core damage probabilities indicate that performing more frequent surveillance tests does not necessarily decrease the risk. In fact, there exists an optimal test frequency beyond which the probability of core damage starts to increase. This optimal test frequency is of significance in practice.