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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.
Y. D. Lee, S. Y. Oh, J. H. Chang
Nuclear Science and Engineering | Volume 151 | Number 3 | November 2005 | Pages 319-334
Technical Note | doi.org/10.13182/NSE05-A2551
Articles are hosted by Taylor and Francis Online.
Neutron data for total and capture cross sections were evaluated on 160Dy, 161Dy, 162Dy, 163Dy, and 164Dy up to 20 MeV. The resolved resonance parameters were adopted from the Mughabghab compilation, but one bound level resonance for each isotope except 162Dy was invoked to reproduce the reference thermal cross sections. The average resonance parameters for s-wave neutrons were obtained from the analysis of the statistical behavior of resolved resonance parameters. Recent measurements of the capture cross sections were taken into account in adjusting the average resonance parameters for p- and d-waves. From the first excited energy to 20 MeV, the optical model, Hauser-Feshbach model, and quantum mechanical models were used to produce total, elastic scattering, and capture cross sections. The energy-dependent optical model potential was decided based on the recent experimental data. The calculated cross sections were in good agreement with the experimental data. The present evaluation resulted in improvement over the ENDF/B-VI.7 code.