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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.
Chenghui Wan, Wenchang Dong, Lin Guo, Jiahe Bai
Nuclear Science and Engineering | Volume 197 | Number 7 | July 2023 | Pages 1454-1466
Technical Paper | doi.org/10.1080/00295639.2022.2158704
Articles are hosted by Taylor and Francis Online.
The “two-step” scheme based on assembly homogenization is widely applied in simulations for pressurized water reactor (PWR) cores in which the few-group constants of the fuel assembly are generated with the single-assembly simulation. However, the reflective boundary condition adopted in the single-assembly simulation can’t characterize the real environment in the core, especially the strong heterogeneity between the neighboring assemblies. In order to consider the environmental effects on the homogenized few-group constants, a rehomogenization method is proposed. In this method, the heterogeneous neutron spectral of single-assembly model of the reflective boundary condition is corrected with the homogeneous neutron spectral of the real core environment. Through definition and precalculation of the rehomogenization factors for few-group constants during the fuel assembly simulation, corresponding corrected constants can be recomputed during the core simulation to consider the environmental effects. This method has been implemented in our home-developed code Bamboo-C. For method verification, both the heavy reflector PWR EPR1750 and the baffle reflector PWR HPR1000 have been simulated. It can be observed that the biases of the eigenvalues can be notably reduced with the proposed rehomogenization method. The assembly-averaged powers of the peripheral fuel assemblies were also notably reduced, especially for the EPR1750, which indicates that the environmental effects can be appropriately solved with the rehomogenization method.