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Denver, CO|Sheraton Denver
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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.
D. A. Powers
Nuclear Science and Engineering | Volume 88 | Number 3 | November 1984 | Pages 357-366
Technical Paper | doi.org/10.13182/NSE84-A18589
Articles are hosted by Taylor and Francis Online.
Molten stainless steel at ∼1720°C and melts of iron and alumina or 54 wt% UO2, 16 wt% ZrO2, and 30 wt% stainless steel at 2400 to 2800°C were poured onto 0.95- to 7.62-cm-thick steel structures. The melts rapidly penetrated these structures, probably by a thermal ablation process. Coatings of 0.2- to 2-mm-thick urania on the surfaces of the steel delayed penetration by the very high-temperature melts. Data from tests involving melts impinging on steel structures could be correlated by the single-parameter, empirical expression A finite difference model of the experiments is described. The model is used as the basis for predicting the extent of crust formation when melts contact cold steel and to suggest that a gas gap may form between the steel and any crust of frozen material that does form.