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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.
Martin Frank, Jonas Kusch, Thomas Camminady, Cory D. Hauck
Nuclear Science and Engineering | Volume 194 | Number 11 | November 2020 | Pages 971-988
Technical Paper | doi.org/10.1080/00295639.2020.1730665
Articles are hosted by Taylor and Francis Online.
Solving the radiative transfer equation with the discrete ordinates (S) method leads to a nonphysical imprint of the chosen quadrature set on the solution. To mitigate these so-called ray effects, we propose a modification of the S method that we call artificial scattering S (as-S). The method adds an artificial forward-peaked scattering operator that generates angular diffusion to the solution and thereby mitigates ray effects. Similar to artificial viscosity for spatial discretizations, the additional term vanishes as the number of ordinates approaches infinity. Our method allows an efficient implementation of explicit and implicit time integration according to standard S solver technology. For two test cases, we demonstrate a significant reduction of error for the as-S method when compared to the standard S method, both for explicit and implicit computations. Furthermore, we show that a prescribed numerical precision can be reached with less memory due to the reduction in the number of ordinates.