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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.
Jinzhao Zhang, Adrien Dethioux, Andriy Kovtonyuk, Christophe Schneidesch
Nuclear Technology | Volume 205 | Number 1 | January-February 2019 | Pages 140-152
Technical Paper | doi.org/10.1080/00295450.2018.1516055
Articles are hosted by Taylor and Francis Online.
In the framework of the Organisation for Economic Co-operation and Development/Nuclear Energy Agency PREMIUM [Post-BEMUSE (Best-Estimate Methods Uncertainty and Sensitivity Evaluation) REflood Model Input Uncertainty Methods] benchmark (2012–2015), Tractebel has contributed to the development and the proof-of-concept application of a sampling-based inverse uncertainty quantification (IUQ) approach with the DAKOTA statistical uncertainty and sensitivity analysis tool. This IUQ approach has been applied to quantify the RELAP5/MOD3.3 reflood-related model input uncertainties, based on selected reflood tests [FEBA (Flooding Experiments with Blocked Arrays) and PERICLES]. This paper presents the Tractebel IUQ approach as well as the results of applications to the PREMIUM benchmark. Lessons learned and perspectives for future development are also discussed.