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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.
L. Green, J. A. Mitchell, N. M. Steen
Nuclear Science and Engineering | Volume 52 | Number 3 | November 1973 | Pages 406-412
Technical Note | doi.org/10.13182/NSE73-A19488
Articles are hosted by Taylor and Francis Online.
The 233U fission neutron spectrum has been measured by pulsed-beam time-of-flight techniques from 0.8 to 10 MeV. Above ≈2 MeV, the data were found, within statistics, to be adequately represented by either the model in the ENDF/B-III file or a best fit Maxwellian distribution with nearly the same average energy. At lower energy, the data appear to follow the ENDF/B representation somewhat more closely. The fit of a Maxwellian distribution to the 233U data yielded an average “temperature” parameter of 1.34 ± 0.02 MeV, where the error includes both statistical and systematic uncertainties. A similar fit to data taken for a 235U sample yielded a temperature parameter of 1.31 ± 0.03 MeV; however, the best estimated difference in temperature is 16 ± 6 keV.
