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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.
David J. Loaiza, Rene Sanchez, Roger Brewer
Nuclear Science and Engineering | Volume 143 | Number 2 | February 2003 | Pages 132-140
Technical Paper | doi.org/10.13182/NSE03-A2324
Articles are hosted by Taylor and Francis Online.
Critical experiments are carried out in order to validate, improve, and benchmark the extensive data calculations available. A series of such experiments was performed at the Los Alamos Criticality Experiments Facility. These experiments were performed to provide criticality safety data for waste matrix materials. These critical experiments were fueled with highly enriched uranium, moderated and reflected with polyethylene, and mixed with silicon dioxide (SiO2), aluminum (Al), magnesium oxide (MgO), and gadolinium (Gd). The uncertainties affecting the experiment were divided into three broad categories: mass measurement, geometry, and material composition. Each category is considered in turn, and then the total experimental uncertainty is derived. All four experiments had a measured keff of 1.001. The sensitivity analyses of these critical experiments yielded uncertainties in the measured keff of ±0.0026 for SiO2, ±0.0026 for Al, ±0.0021 for MgO, and ±0.0029 for Gd. These experiments were judged to be of benchmark quality.