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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.
N. J. Peters, J. C. McKibben, K. Kutikkad, W. H. Miller
Nuclear Science and Engineering | Volume 171 | Number 3 | July 2012 | Pages 210-219
Technical Paper | doi.org/10.13182/NSE10-71
Articles are hosted by Taylor and Francis Online.
A detailed study at the Missouri University Research Reactor indicates that limitations in the energy balance methodology, using the Monte Carlo N-Particle transport code (MCNP) and the Evaluated Nuclear Data Files (ENDF), affect the accuracy of predicting important parameters for reactor physics studies. In the case of fuel conversion, key parameters such as flux and power level cannot be measured until the converted reactor is operating. Therefore, predictions with well-known uncertainties are essential for an effective conversion. However, due to inherent energy balance problems in the isotopic heating evaluations for materials within various fuel matrices, in particular the U-10Mo monolithic fuel, the values for the predicted parameters could vary more than previously estimated. In particular, the total recoverable energy per fission, which directly affects the calculated flux for a given power level, appears to be underestimated by MCNP's energy balance method. Therefore, an alternative methodology for predicting the total recoverable energy of a system was investigated. Results for the proposed low-enriched uranium U-10Mo configuration show that there is a 3.02-MeV difference between the total recoverable energy per fission from this work and that from the MCNP predictions. A similar comparison for the present highly enriched uranium UAlx configuration shows a difference of 1.24 MeV.