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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.
Osamu Mitarai, Katsunori Muraoka
Fusion Science and Technology | Volume 36 | Number 2 | September 1999 | Pages 194-211
Technical Paper | doi.org/10.13182/FST99-A102
Articles are hosted by Taylor and Francis Online.
The consequence of the failure effect of burn control diagnostic systems, such as neutron diagnostics, bolometers, electron cyclotron emission power loss diagnostics, interferometer, and lost alpha detector, on ignited operation has been analyzed, and the fail-safe operation in a tokamak fusion reactor including the International Thermonuclear Experimental Reactor (ITER) has been considered. Because the failure of the neutron diagnostic system for fusion power measurement leads to a fusion power surge for the simple control algorithm, the fail-safe control algorithm has been introduced to avoid this problem. As failure of the power loss measurement such as the bolometer system terminates the ignition, then it is less problematic. The effect of the interferometer fringe counting error on the ignited operation is not simple, as just mentioned, and a lost alpha detector can be removed from the feedback system using the preset value.