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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.
D. S. Rowe, D. E. McFeron
Nuclear Science and Engineering | Volume 26 | Number 3 | November 1966 | Pages 319-328
Technical Paper | doi.org/10.13182/NSE66-A17352
Articles are hosted by Taylor and Francis Online.
This paper presents a mathematical model that describes the heat transfer in a defectively bonded flat-plate fuel element. The bond defect is assumed to exist only on one side of the fuel plate and to be either a circular spot or infinite strip in shape. Details of the general solution to the heat conduction equation for the mathematical model are shown for the strip-type defect. For a particular type of defect, the temperature distribution is dependent upon three dimensionless parameters that include the effects of defect size and the heat transfer properties of the defective fuel element. Data are provided in terms of the three dimensionless parameters that permit rapid estimates of fuel temperatures in fuel plates with strip and spot defects. These defects are assumed to be step reductions in the normal fuel-boundary conductance. Defect sizes on the order of a couple of fuel thicknesses can cause significant local increases in the fuel temperature and fuel-surface heat flux.