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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.
H. F. McFarlane, S. G. Carpenter, P. J. Collins, D. N. Olsen, S. B. Brumbach
Nuclear Science and Engineering | Volume 87 | Number 3 | July 1984 | Pages 204-232
Technical Paper | doi.org/10.13182/NSE84-A17779
Articles are hosted by Taylor and Francis Online.
Experimental programs to investigate the physics characteristics of heterogeneous liquid-metal fast breeder reactor cores have been conducted in the zero-power plutonium reactor critical facility over a period of ∼ 5 yr. Previous experiments on conventional homogeneous cores provided appropriate benchmark data against which to judge the heterogeneous core results. For a heterogeneous reactor of the Clinch River Breeder Reactor size, both the physics parameters and the ability to predict them by common design methods differ substantially from an equivalent conventional design. Data errors and methods approximations have a greater effect in the analysis of heterogeneous cores, particularly with respect to such spatially varying parameters as power distributions and control rod worths. Preliminary results from recent experiments on a 700-MW(electric)-sized heterogeneous assembly are presented. As expected, predictions of physics parameters in general are worse than for conventional cores. Eigenvalue spectra and cross-section sensitivity have been used to characterize the spatial sensitivity of the cores.