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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.
Yukio Oyama, Kazuaki Kosako, Hiroshi Maekawa
Nuclear Science and Engineering | Volume 115 | Number 1 | September 1993 | Pages 24-37
Technical Paper | doi.org/10.13182/NSE93-A35519
Articles are hosted by Taylor and Francis Online.
Angular neutron flux spectra leaking from iron slabs with various thicknesses up to 600 mm have been measured by the time-of-flight technique. The results are compared with calculations by the MCNP Monte Carlo code and the DOT3.5 two-dimensional discrete ordinates code with the JENDL-3 nuclear data file and with ENDF/B-IV. In the DOT3.5 calculations, a cross-section set with a selfshielding correction factor is also applied to examine its effect. The results show that the MCNP calculations based on both files agree very well for the main part of the deeply penetrating neutron spectrum, but the DOT3.5 code without a self-shielding correction underestimates the high-energy flux and the flux in the resonance energy range with increasing slab thickness. The self-shielding correction factor improves the underestimation, but the calculated flux is still smaller than the MCNP calculation.