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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.
D. D. Lanning
Nuclear Technology | Volume 56 | Number 3 | March 1982 | Pages 565-574
Technical Paper | Nuclear Fuel | doi.org/10.13182/NT82-A32915
Articles are hosted by Taylor and Francis Online.
Thermally induced cracking of the UO2 fuel pellets undoubtedly results in some reduction of the effective fuel thermal conductivity, relative to that for solid UO2. This effect may be approximated by appropriately chosen “crack factors” that reduce the solid-UO2 thermal conductivity. We demonstrate that the assumption of reduced fuel conductivity always results in a reduction of the fuel stored energy that is inferred from fuel centerline temperature data. This reduction occurs whether the crack factors are introduced as simple constants or as functions of radial position within the fuel pellet. If fuel performance computer codes remain “tuned” to the current body of centerline temperature data, those codes will predict lower fuel stored energy when fuel cracking is taken into account regardless of the modeling assumptions invoked. Accounting for fuel cracking should lead to a reduction in calculated peak cladding temperatures obtained in some loss-of-coolant accident simulations.