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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.
J. R. Ferron, P. B. Snyder
Fusion Science and Technology | Volume 48 | Number 2 | October 2005 | Pages 931-944
Technical Paper | DIII-D Tokamak - Achieving Reactor-Level Plasma Pressure | doi.org/10.13182/FST05-A1049
Articles are hosted by Taylor and Francis Online.
The experimental and modeling results on H-mode edge-localized mode (ELM) instabilities from the DIII-D tokamak project are reviewed. This work has led to the conclusion that the most common type of ELM, called Type I, is triggered by a coupled peeling-ballooning instability driven by the pressure gradient and current density in the H-mode edge pedestal region. Good agreement is found between theoretically predicted stability boundaries and toroidal mode numbers for this instability and experimental observations of edge pedestal parameters and ELM amplitude and frequency as a function of discharge shape and edge-region collisionality. The range of toroidal mode numbers for which there is access to a second stability regime is shown to play an important role. This model of H-mode edge stability has been used to predict the pedestal parameters for ITER and FIRE.