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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.
Wadim Jaeger, Victor Hugo Sanchez Espinoza
Nuclear Technology | Volume 184 | Number 3 | December 2013 | Pages 333-350
Technical Paper | Thermal Hydraulics | doi.org/10.13182/NT184-333
Articles are hosted by Taylor and Francis Online.
The validation of computer codes related to the thermal-hydraulic analyses of nuclear reactors is a challenging undertaking because of the complexity of the phenomena involved, e.g., boiling, condensation, and mixing. In the frame of the ongoing validation of the best-estimate system code TRACE, the present paper focuses on the phenomena taking place during the quenching of the hot surface of the fuel rod simulator with cold water. Since TRACE describes the physical phenomena with empirical correlations derived from experiments, it is necessary to ensure that these correlations are valid if applied to similar experiments but different boundary conditions. By means of an uncertainty and sensitivity study, the influence of the empirical models and their associated uncertainties on selected output parameters is quantified and the parameters with the largest sensitivity are evaluated.