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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.
Jonas Berger, Alexander Mühle, Kai-Martin Haendel
Nuclear Science and Engineering | Volume 194 | Number 6 | June 2020 | Pages 415-421
Technical Paper | doi.org/10.1080/00295639.2019.1705656
Articles are hosted by Taylor and Francis Online.
During the lifetime of fuel assemblies, irradiation and fluid mechanical forces can cause a permanent deformation in the lateral direction that leads to larger interassembly water gaps in the reactor core. The standard reload safety analysis for the reactor core is developed for a uniform distribution of corewise interassembly water gaps. A nonuniform distribution of water gaps with locally larger or smaller water gaps could lead to a significant change in the positions of the hot-spot factors. Thus, such modifications could also impact boundary conditions for safety analysis or boundary conditions of the reactor core surveillance systems. To analyze the impact of a nonuniform water-gap distribution on the safety analysis and the reactor core surveillance systems, TÜV Nord EnSys is developing a new methodology that allows the incorporation of assembly bow effects in core analysis. For this methodology, functions linking the maximal relative power increase in the vicinity of the modified water gap to the fuel properties had to be derived. This was accomplished by simulating for gaps between different fuel types at selected positions in a full-core model of a generic four-loop Siemens/Kraftwerk Union pressurized water reactor using the bow model of the two-group diffusion code SIMULATE-3. The data of the maximal relative power increase were linearly correlated with the spectral indices and the coolant densities of the two gap-adjacent assemblies. Then a function was derived that provides a firsthand approximation of the maximal relative power increase using only the physical properties of the unbowed core configuration. The maximal absolute positive deviation of the function from the simulation results was 2.4%.