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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.
W. L. Barr, R. H. Bulmer, L. J. Perkins, S. A. Cohen, K. A. Werley
Fusion Science and Technology | Volume 21 | Number 3 | May 1992 | Pages 1416-1420
International Thermonuclear Experimental Reactor | doi.org/10.13182/FST92-A29920
Articles are hosted by Taylor and Francis Online.
We have just completed a comparison of predictions for the scrape-off layer (SOL) plasma, from a physics model [1] with the more accurate ones from a two-dimensional fluid code, the B2 code [2]. The results presented here show rather good agreement on values of plasma temperature in the SOL and of divertor heat load, for a rather wide range of Tokamak sizes and parameters. We are therefore confident that this model will provide a suitable divertor module for both the new ITER systems code, SUPERCODE [3], and other applications requiring fast but accurate modelling of edge plasma parameters, at least within the range of the present benchmarks.