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2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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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.
Young-Sik Cho, Young-Ouk Lee
Nuclear Science and Engineering | Volume 177 | Number 1 | May 2014 | Pages 90-96
Technical Paper | doi.org/10.13182/NSE12-96
Articles are hosted by Taylor and Francis Online.
Recent evaluations of neutron cross-section covariances in the resolved resonance region reveal the need for further research in this area. Major issues include declining uncertainties in multigroup representations and the proper treatment of scattering radius uncertainty. To address these issues, the present work develops a formalism and computer code based on a multilevel Breit-Wigner formula, extending the previous work based on the kernel approximation, using resonance parameter uncertainties from the Atlas of Neutron Resonances. Analytical expressions derived for average cross-section uncertainties in the arbitrary energy bin along with their sensitivities provide a fundamental tool for determining the cross-section uncertainties. The role of resonance-resonance and resonance-potential scattering correlations is studied. As a test case, we apply this approach to estimate (n,γ) and (n,el) covariances for the structural material 55Mn and compare the results with those from the previous kernel approximation.
