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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. Bando, K. Ohya, K. Inai
Fusion Science and Technology | Volume 60 | Number 4 | November 2011 | Pages 1467-1470
Interaction with Materials | Proceedings of the Ninth International Conference on Tritium Science and Technology (Part 2) | doi.org/10.13182/FST11-A12708
Articles are hosted by Taylor and Francis Online.
In order to simulate carbon deposition profile in the divertor of ITER, long-distance transport in the scrape-off-layer and divertor plasma of carbon and hydrocarbons eroded from the divertor target plates are modeled. Physically eroded carbons dominate a sharp profile on the outer target plate, whereas at the inner target plate, a very small redeposition is observed. Chemically eroded hydrocarbons produce a redeposition on the dome area as well as both inner and outer target plates. Assuming tritium content in the redeposited layers, tritium co-deposition profile on the inner and outer target plates and dome is estimated, which allows us to predict the long-term tritium retention in the divertor of ITER.