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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.
D. Testa, H. Carfantan, R. Chavan, J. B. Lister, J-M. Moret, M. Toussaint
Fusion Science and Technology | Volume 57 | Number 3 | April 2010 | Pages 238-273
Technical Paper | doi.org/10.13182/FST10-A9469
Articles are hosted by Taylor and Francis Online.
The measurement performance of the baseline system design for the ITER high-frequency magnetic diagnostic system and attempts at its optimization have been performed using an innovative method based on the sparse representation of signals and the minimization of the maxima of the spectral window for integer mode numbers. This analysis has led to the conclusion that 350 to 500 sensors are in fact needed to satisfy the ITER requirements for the measurement performance and the risk management over the machine lifetime, instead of the originally foreseen approximately 170 sensors. In the companion paper we have presented the general summary results of our work; here we present a more complete overview of the analysis method and further details of our test calculations.