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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.
Gabriel Kooreman, Farzad Rahnema
Nuclear Technology | Volume 192 | Number 3 | December 2015 | Pages 264-277
Technical Paper | Radiation Transport and Protection | doi.org/10.13182/NT14-150
Articles are hosted by Taylor and Francis Online.
The hybrid Diffusion-Transport Homogenization (DTH) method has been improved by replacing the assembly-level fixed-source calculation step with a fixed number of whole-core transport sweeps following each homogenization step. Like the unmodified DTH method, the Enhanced hybrid Diffusion-Transport Homogenization (EDTH) method adds an “auxiliary cross-section” term to the right side of the transport equation in order to maintain consistency with the heterogeneous equation. As an improvement to the DTH method, the on-the-fly rehomogenization step of the EDTH method utilizes a fixed number of full-core transport sweeps in lieu of assembly-level fixed-source heterogeneous transport calculations. The EDTH method has been tested in one-dimensional reactor core benchmark problems typical of a boiling water reactor core, a gas-cooled thermal reactor [High Temperature Test Reactor (HTTR)] core, and a pressurized water reactor core with mixed-oxide fuel. The method has been shown to reproduce the heterogeneous transport flux profile with 0 to 46 pcm eigenvalue error and 0.1% to 1.8% mean relative flux error with a speedup factor of 1.4 to 4.5 times faster than the DTH method. This represents a speedup of 3.0 to 12.5 times compared to fine-mesh transport.