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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.
P. E. Labeau, Z. Ould Amar
Nuclear Science and Engineering | Volume 126 | Number 2 | June 1997 | Pages 146-157
Technical Paper | doi.org/10.13182/NSE97-A24468
Articles are hosted by Taylor and Francis Online.
Monte Carlo games especially designed for probabilistic dynamics problems have been shown to be very efficient for the calculation of a pressurized water reactor (PWR) pressurizer unreliability. However, these methods rely on the implicit hypothesis that transition rates and probabilities, as well as control means response times, can be precisely determined. But reality is different: Because of a lack of knowledge, only crude estimations of transition rates can be obtained. Moreover, control device response times cannot be assumed constant for rapid transients. Therefore, considering distributed values of these quantities seems more realistic. Several attempts to take into account these uncertainties, while conserving as many advantages as possible of the high-efficiency simulation techniques, are summarized. The PWR pressurizer application is used to compare the capabilities of the proposed methods.