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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.
David L. Aumiller, Jeffrey W. Lane
Nuclear Science and Engineering | Volume 184 | Number 3 | November 2016 | Pages 463-471
Technical Paper | doi.org/10.13182/NSE16-12
Articles are hosted by Taylor and Francis Online.
COBRA-IE is a three-field subchannel analysis code that was originally based on the COBRA-TF code series. The default interfacial drag model in COBRA-IE has been assessed against a wide range of pressure drop data taken in confined geometries and has been shown to perform very well. The difference in interfacial drag behavior for confined flow paths compared to large open regions where the bubbles are not constrained by the physical geometry of the flow path has been well documented in the open literature. Therefore, a dedicated interfacial drag model for large, open regions has been developed and implemented in COBRA-IE. This alternative interfacial drag model is based on the drift flux formulation and is activated by user input. A combination of the Kataoka-Ishii and the Zuber-Findley drift flux correlations has been implemented in COBRA-IE to calculate the weighted mean drift velocity and distribution parameter. The implementation of the model is described in this paper, and the interface functions to transition between the drift flux and two-fluid formulations are emphasized.
An assessment of the predictive capability of COBRA-IE for the transient level swell phenomena for the experiments performed by General Electric (GE) has been performed. Level swell is an important phenomenon for reactor safety analysis because it impacts water distribution within the reactor vessel during the blowdown phase of the transient as well as the residual inventory available to provide core cooling. The initial assessment of the code using the default interfacial drag modeling package showed an overprediction of the level swell and liquid carryover for the GE experiments, which is indicative of an overprediction of the interfacial drag for these situations. In addition to using the new code to reexamine the GE level swell experiment, assessments of the new model have been performed using the steady-state void fraction data collected in the Beattie-Sugawara and Smith experiments and are presented in this paper.