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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.
K. A. Alfieri, R. C. Block, P. J. Turinsky
Nuclear Science and Engineering | Volume 51 | Number 1 | May 1973 | Pages 25-31
Technical Paper | doi.org/10.13182/NSE73-A23254
Articles are hosted by Taylor and Francis Online.
Low resolution transmission experiments on 14- and 20-in.-thick samples of iron have been conducted at Rensselaer Polytechnic Institute’s linear accelerator to evaluate the adequacy of various data files in predicting total neutron cross-section minima from 24 to 750 keV. From our transmission area analysis we conclude that both the Penny-Kinney file and Version-19 file (incorporating the Columbia minima measurement) generally overestimate the total cross section in the region of minima, with the Version-19 file strongly preferred for accurate minima prediction. With the ENDF/B-III (MAT 1180) file identical to the Penny-Kinney file (except about the 24-keV minima), similar negative conclusions apply. At approximately the 24-keV minima where our resolution is sufficient to evaluate θt(E), we obtain excellent agreement with ENDF/B-III (MAT 1180). We quote (σt)min = 0.42 ± 0.03 b at E = 24.3 ± 0.1 keV.
