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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.
Peter G. Laky, Nicholas Tsoulfanidis
Nuclear Science and Engineering | Volume 121 | Number 3 | December 1995 | Pages 433-447
Technical Paper | doi.org/10.13182/NSE95-A24145
Articles are hosted by Taylor and Francis Online.
Pressure vessel fluence and reaction rates for dosimetry foils in the cavity surrounding the pressure vessel of a pressurized water reactor were determined with a Monte Carlo calculation using the MCNP code. Source neutrons were sampled from a position probability distribution derived from the utility-provided normalized assembly segment power output. The MCNP model was based on one-eighth core symmetry. Source segment spatial biasing, energy cutoff, spatial importance functions, and weight windows were employed as variance reduction techniques. Computed reaction rates were compared with measured ones and in one case to discrete ordinates transport code calculations. Computed reaction rates matched the measured ones within ±10% for 21 of 33 cases and within ±15% for 26 of 33 cases. Neutron flux and fluence >0.1111 and 1 MeV at the pressure vessel location were computed to <10% statistical uncertainty. The estimated maximum fluence per cycle was found to be of the order of 1017 n/cm2.