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2026 ANS Annual Conference
May 31–June 3, 2026
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.
R. W. Ostensen, R. J. Lipinski
Nuclear Science and Engineering | Volume 79 | Number 1 | September 1981 | Pages 110-113
Technical Note | doi.org/10.13182/NSE81-A19046
Articles are hosted by Taylor and Francis Online.
A model for particle bed dryout based on the phenomenon of flooding is developed for particles greater than ∼1 mm in diameter. Dryout develops when vapor flow from boiling in the bed limits the influx of replenishing coolant. In the flooding model, the liquid-vapor counterflow is limited by the drag between the liquid and the vapor. In previous models, the counterflow is limited by the drag between the coolant and the bed particles. The flooding model predicts a dryout heat flux that depends on the square root of the diameter of the particles. Previous dryout models predict a dependence on the square of the diameter. The flooding model predicts significantly lower dryout heat fluxes for particle diameters in excess of ∼1 mm. These predictions agree well with experimental data.