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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.
S. Nakamura
Nuclear Science and Engineering | Volume 61 | Number 1 | September 1976 | Pages 98-106
Technical Paper | doi.org/10.13182/NSE76-A28465
Articles are hosted by Taylor and Francis Online.
The accelerating effect of coarse-mesh rebalancing on the low-order Chebyshev polynomial iterations to obtain the fundamental eigenvector of large homogeneous linear systems associated with elliptic partial-differential equations is mathematically analyzed. Coarse-mesh rebalancing is shown to have a positive accelerating effect if one of the following conditions is met: (a) the weighting vectors are not contaminated with high eigenvector components, (b) Galerkin's weighting vectors are used, or (c) the non-Galerkin weighting vectors are similar to the trial vectors. As another interesting result, it is shown that the overshooting effect is related to the fourth and higher eigenvector components that have spatially odd parities. If the above condition, (c), is met, there is no overshooting; otherwise, the acceleration effect with non-Galerkin weighting vectors is unpredictable.