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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. R. Fawcett, Jr.
Nuclear Science and Engineering | Volume 113 | Number 2 | February 1993 | Pages 173-183
Technical Paper | doi.org/10.13182/NSE93-A24006
Articles are hosted by Taylor and Francis Online.
Tritium production in a sphere of 6LiD with an Oralloy core irradiated by a central source of 14-MeV neutrons has been calculated and compared with experimental measurements. The experimental assembly consisted of an Oralloy sphere surrounded by three solid 6LiD concentric shells with ampoules of 6LiH and 7LiH located in several positions throughout the assembly. The Los Alamos Monte Carlo Neutron Photon Transport Code (MCNP) was used to calculate neutron transport throughout the system and tritium production in the ampoules. The MCNP calculations were three-dimensional and employed ENDF/B- V cross sections. The overall experimentally observed-to-calculated ratios of tritium production were 0.996 (±2.5%) in 6LiH ampoules and 0.903 (±5.2%) in 7LiH ampoules. Tritium production in a sphere of 6LiD without an Oralloy core has been reanalyzed using ENDF/B-V cross sections, and the results are reported. The reanalyzed observed-to-calculated values of tritium production were 1.053 (±2.1%) in 6LiH and 0.999 (±2.1%) in 7LiH. The foregoing several uncertainties do not include an estimated <6% systematic error in the observed values.