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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.
Alan J. Wootton, Steven C. McCool, Shaobai Zheng
Fusion Science and Technology | Volume 19 | Number 3 | May 1991 | Pages 473-491
Technical Paper | Divertor System | doi.org/10.13182/FST91-A29388
Articles are hosted by Taylor and Francis Online.
A simple test particle model that attempts to describe particle motion in the presence of intrinsic electrostatic fluctuations in a prescribed tokamak magnetic field is presented. In particular, magnetic field configurations that include externally produced magnetic islands and stochastic regions are considered. The resulting test particle transport is compared with the predictions of analytic models and with the experimentally measured electron heat and particle transport on the Texas Experimental Tokamak (TEXT). Agreement between the test particle results and applicable analytic theories is found. However, there is only partial agreement with the experimental results, and possible reasons for the discrepancies are explored. Good agreement is found between predicted and measured spatially asymmetric particle distributions. The particle collection efficiency of an apertured limiter inside a magnetic island (an intra-island pump limiter) is discussed.