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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.
John F. Carew, Kai Hu, Gabriel Zamonsky
Nuclear Science and Engineering | Volume 136 | Number 2 | October 2000 | Pages 282-293
Technical Paper | doi.org/10.13182/NSE99-96
Articles are hosted by Taylor and Francis Online.
Recently, a uniform equal-weight quadrature set, UEn, and a uniform Gauss-weight quadrature set, UGn, have been derived. These quadratures have the advantage over the standard level-symmetric LQn quadrature sets in that the weights are positive for all orders,and the transport solution may be systematically converged by increasing the order of the quadrature set. As the order of the quadrature is increased,the points approach a uniform continuous distribution on the unit sphere,and the quadrature is invariant with respect to spatial rotations. The numerical integrals converge for continuous functions as the order of the quadrature is increased.The numerical characteristics of the UEn quadrature set have been investigated previously. In this paper, numerical calculations are performed to evaluate the application of the UGn quadrature set in typical transport analyses. A series of DORT transport calculations of the >1-MeV neutron flux have been performed for a set of pressure-vessel fluence benchmark problems. These calculations employed the UGn (n = 8, 12, 16, 24, and 32) quadratures and indicate that the UGn solutions have converged to within ~0.25%. The converged UGn solutions are found to be comparable to the UEn results and are more accurate than the level-symmetric S16 predictions.