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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.
C. L. Brown, L. E. Hansen, H. Toffer
Nuclear Science and Engineering | Volume 35 | Number 3 | March 1969 | Pages 358-363
Technical Paper | doi.org/10.13182/NSE69-A20014
Articles are hosted by Taylor and Francis Online.
Exponential and critical approach experiments have been performed to determine material buddings and extrapolation distances for several hexagonal lattice arrays of 2.1 wt% 235U enriched uranium tubes in light water. Tubes of two sizes were measured—2.33-in. o.d., 1.77-in. i.d.; and 1.38-in. o.d., 0.63-in. i.d. The arrays included clean lattices of uranium tubes; uranium tubes containing lithium aluminate target rods; uranium tubes with adjacent neutron absorbing columns; and two mixed lattices of 0.95 and 2.1 wt% enriched tubes—one with the 0.95 and 2.1 wt% tubes evenly distributed in the lattice, and the other with the 0.95 and 2.1 wt% tubes arranged in alternate rings. These experiments supplement data obtained in 1965 for 1.002, 1.25, and 1.95 wt% enriched uranium tubes. Critical parameters for these lattices, calculated with the HAMMER code, agree reasonably well with the measured results.