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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.
Mo-Chen Hsu
Nuclear Technology | Volume 79 | Number 3 | December 1987 | Pages 274-283
Technical Paper | Fission Reactor | doi.org/10.13182/NT87-A34017
Articles are hosted by Taylor and Francis Online.
The time series modeling approach is introduced to estimate the prompt-neutron decay constant. Neutron flux noise data of three fuel cycles of a high flux isotope reactor are analyzed. The noise data detected from an ionization chamber outside the reactor core surrounded by a beryllium reflector were recorded at full-power operation. The decay constant corresponding to a rounded-off corner break frequency can be estimated from the characteristic roots of adequate autoregressive moving average models. This implicit characteristic identification is one of the advantages of off-line modeling analysis. The estimated neutron lifetime in the beginning of fuel cycle is 38 µs (expected value = 35 µs). The estimated lifetime near the end of cycle is 66 µs (expected value = 70 µs).