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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.
Thomas K. S. Liang, Huan-Jen Hung, Chin-Jang Chang
Nuclear Technology | Volume 136 | Number 3 | December 2001 | Pages 292-300
Technical Paper | Thermal Hydraulics | doi.org/10.13182/NT01-A3246
Articles are hosted by Taylor and Francis Online.
With the consideration of mass unbalance, coolant shrinking, and compressibility, a model for reactor coolant leakage evaluation has been developed to quantify on-line the system leakage rate with conventional system measurements, regardless of where the leak occurs. This model has been derived from the system of total continuity, and it divides the reactor coolant system (RCS) into two regions, namely, the saturated and subcooled regions. The pressurizer is considered as a saturated region, and the remaining part of the RCS is regarded as a subcooled region. Taking the on-line measurements of the RCS including the RCS pressure, temperature, pressurizer water level, and charging and letdown flow rates, this model can directly evaluate on-line the RCS leakage rate. It is noted that this model is applicable only if the RCS remains subcooled. To verify the applicability of this model, data generated by RELAP5/MOD3 simulation and experimental measurements from the Institute of Nuclear Energy Research, Taiwan, Integral System Test Facility were adopted to assess this model. With further on-line verification against the Maanshan training simulator, this model was finally delivered to the Maanshan nuclear power plant (a three-looped Westinghouse pressurized water reactor) to assist the operator training and on-line evaluation of the RCS leakage rate. The smallest amount of leak flow that can be detected by the ROCK model is 3 gal/min.