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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.
M. Yoda, S. I. Abdel-Khalik, D. L. Sadowski, B. H. Mills, J. D. Rader
Fusion Science and Technology | Volume 67 | Number 1 | January 2015 | Pages 142-157
Technical Paper | doi.org/10.13182/FST14-792
Articles are hosted by Taylor and Francis Online.
Current predictions suggest that the target plate of a divertor, as one of the few solid surfaces directly exposed to the plasma of a magnetic fusion energy reactor, will be subject to steady-state heat fluxes as great as 10 MW/m2. Developing appropriate methods for cooling these divertors with helium is therefore a major technological challenge for plasma-facing components. This paper reviews dynamically similar experimental studies and numerical simulations of the thermal-hydraulic performance of two helium-cooled divertor concepts, the helium-cooled divertor with multiple-jet cooling (HEMJ) and the helium-cooled flat plate divertor, as well as a variant of the HEMJ, the so-called finger-type divertor, performed as part of the ARIES study. The results from these studies are extrapolated to prototypical conditions and used to predict the maximum average heat flux and coolant pumping power requirements for these divertor concepts. These extrapolations can be used to estimate how changes in the operating conditions, such as the helium inlet temperature and the maximum temperature of the divertor pressure boundary, affect thermal performance. Finally, the correlations from these extrapolations are used in the system code developed by the ARIES study.