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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.
T. Eich, A. Werner
Fusion Science and Technology | Volume 53 | Number 3 | April 2008 | Pages 761-779
Technical Paper | doi.org/10.13182/FST08-A1733
Articles are hosted by Taylor and Francis Online.
The heat load due to plasma radiation is estimated for the plasma wall components of the stellarator Wendelstein 7-X (W7-X). A fully three-dimensional Monte Carlo code is used to simulate heating of first-wall components due to photon emission from the plasma. The plasma wall components can be described in a complex way with arbitrary shapes and orientation and flexible numerical representation. The volume radiation distribution is assumed to be described by poloidal symmetric and radially varying one-dimensional profiles aligned to the magnetic flux surfaces. A further example is given by a nonpoloidal symmetric radiation distribution following the five X point regions of the island divertor magnetic structure. Several realistic and artificial radiation profiles are chosen to investigate the local heat loads on an idealized plasma wall. The first detailed technical application of the code is the estimation of the local heat load on the Thomson scattering windows and on the inner surface of several vacuum ports of one half-module of the W7-X plasma vessel.