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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.
Elia Merzari, Hisashi Ninokata, Sheng Wang, Emilio Baglietto
Nuclear Technology | Volume 165 | Number 3 | March 2009 | Pages 313-320
Technical Paper | Thermal Hydraulics | doi.org/10.13182/NT09-A4104
Articles are hosted by Taylor and Francis Online.
The present work considers simulation of free-surface vortices by means of computational fluid dynamics. The issue is relevant for the design of sodium-cooled fast breeder reactors (FBRs). In fact, the eventual entrainment of gas in the reactor core of an FBR may cause abnormal operation condition because of disturbed reactivity.The foci of this work are turbulence modeling and free-surface modeling. Two different approaches are tested in the benchmark case of Moriya et al.: single-phase simulation (through large eddy simulation and detached eddy simulation methodology) and two-phase simulation (combining a volume-of-fluid method with turbulence modeling). Results are in excellent agreement with the experiment for the circumferential velocity in both cases if the grid adopted is sufficiently fine near the vortex core. Through additional grid refinement it is possible to correctly reproduce the shape of the vortex dimple. The code employed is STAR-CD 4.0.