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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.
X. Lefebvre, K. Liger, M. Troulay, N. Ghirelli, C. Perrais
Fusion Science and Technology | Volume 60 | Number 4 | November 2011 | Pages 1276-1279
Environmental and Organically Bound Tritium | Proceedings of the Ninth International Conference on Tritium Science and Technology (Part 2) | doi.org/10.13182/FST11-A12663
Articles are hosted by Taylor and Francis Online.
The oxide mixture MnO2/Ag2O has been identified as one of the best materials to oxidize hydrogen under ambient temperature and atmospheric pressure conditions. Studies have been carried out within the scope of the mitigation of hydrogen risk in fusion reactors and the optimal composition of this mixture has been determined by Chaudron as MnO2/Ag2O 10% wt. Using Maruéjouls' experiments, a model, previously developed to explain the oxidation of hydrogen by copper oxide for helium purification purpose, has been adapted and its simulation capability tested. To achieve this point, an exploratory experiment with a thin MnO2/Ag2O bed has been carried out under low hydrogen initial concentration (130 Vppm) in order to simulate tritium degassing. Although a very good global agreement between the calculations and the experimental points, the model is unable to account for the behaviour of hydrogen breakthrough at the beginning of the experimentation. Thus, enhancements of this model are presented in this paper. Finally, Scanning Electron Microscopy (SEM) analyses confirm the coherence of some assumptions used to solve the model equations.