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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.
F. Gillot, A. Choux, L. Jeannot, G. Pascal, P. Baclet
Fusion Science and Technology | Volume 49 | Number 4 | May 2006 | Pages 626-634
Technical Paper | Target Fabrication | doi.org/10.13182/FST06-A1176
Articles are hosted by Taylor and Francis Online.
The characterization of the solid DT layer, in terms of thickness and roughness, in the LMJ geometry (hohlraum) is not trivial. The DT layer measurements will be done using a Maksutov-Cassegrain telescope, 39 cm away from the target. This telescope will be used to acquire shadowgraphy images and spectral-interferometry measurements. Shadowgraphy imaging probes the DT layer geometry at the equator of the target. Spectral-interferometry gives the DT layer thickness on one spot on the shell, in the polar regions of the target. By scanning around the poles, several points can be acquired to probe the roughness and the local shape of the DT layer at the poles. This paper presents the spectra-interferometry technique and explains how the DT layer thickness could be deduced from channelled spectra. First experimental results on a 125 m thick empty shell are also reported.