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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.
Shih-Ping Kao, Mujid S. Kazimi
Nuclear Technology | Volume 60 | Number 1 | January 1983 | Pages 7-13
Technical Paper | Fission Reactor | doi.org/10.13182/NT83-A33097
Articles are hosted by Taylor and Francis Online.
The prediction of critical heat flux (CHF) in rod bundles has been studied with both subchannel and bundle-average methods. The correlations of Biasi, Bowring, CISE-4, and Barnett were considered. The General Electric 9-rod bundle CHF data were used in the comparisons. Calculations were performed by the two-fluid subchannel code THERMIT-2. The results indicate that the subchannel method yields more conservative CHF predictions than the bundle average method. This is attributed to the two-phase turbulent mixing phenomenon in the bundle, which can be modeled only on a subchannel basis. The results also indicate that the CISE-4 correlation had the smallest error in prediction of transition boiling for both subchannel and bundle-average methods.