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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.
Siyang Huang, Qiqi Yan, Wenxi Tian, G. H. Su, Suizheng Qiu (Xi’an Jiaotong Univ)
Proceedings | Advances in Thermal Hydraulics 2018 | Orlando, FL, November 11-15, 2018 | Pages 44-56
In the nuclear power system, the critical heat flux (CHF) plays a crucial role in the reactor safety analysis. When CHF occurs, it will cause a sudden increase in the surface temperature, which would lead to the failure of fuel claddings and damage of the core. Considering the cross flow between neighboring channels, spacer grids and mixing vanes in the fuel assembly, the local flow conditions and the geometry of the flow channels make the prediction of CHF more complicated. In this paper, the departure from nucleate boiling (DNB) type CHF in rod bundle is investigated based on the coupled analysis of the subchannel method and a CHF mechanism model, i.e. the liquid sublayer dryout model. The liquid sublayer dryout model assumes that there is a thin liquid sublayer underneath a vapor blanket formed by the coalescence of small bubbles near the heated wall. The dryout of this sublayer will be regarded as the CHF occurrence. In present research, the homogeneous flow model is adopted in the subchannel analysis code to predict the local flow conditions for the rod bundle flow subchannels, which will be used as the input parameters for the liquid sublayer dryout model. In order to verify the method above, the predicted results are compared with the CHF Look-Up Table 2006 (LUT-2006) and the predicted results are in good agreement with the data in LUT-2006. In addition, the effects of rod bundle inlet subcooling, mass flux, heated length and motion conditions on CHF are analyzed.