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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.
K. Schmid, M. J. Baldwin, R. P. Doerner, D. Nishijima
Nuclear Technology | Volume 159 | Number 3 | September 2007 | Pages 238-244
Technical Paper | Beryllium Technology | doi.org/10.13182/NT07-A3871
Articles are hosted by Taylor and Francis Online.
The deposition of beryllium (Be) on carbon (C) and tungsten (W) has been studied at the PISCES-B divertor simulator. Samples of C and W were exposed to a deuterium plasma that was seeded with Be from a small effusion cell mounted ~120 mm upstream from the sample. The incident and eroded flux of Be from these samples was monitored through visible light spectroscopy. The surface composition and layer thickness were measured using Auger electron spectroscopy and ion beam analysis. Results on the formation of Be layers on C and W focusing on the layer growth rate and thickness as functions of temperature are presented. Modeling calculations of Be layer formation on graphite can explain the equilibrium surface composition, but a prediction of the layer formation rate is hampered by an incomplete model of the influence of surface morphology on chemical erosion of the surface. For Be layer formation on W, the modeling calculations including Be diffusion and sublimation correctly predict the Be uptake into the W surface.