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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.
Hiroyasu Mochizuki
Nuclear Technology | Volume 170 | Number 1 | April 2010 | Pages 90-99
Technical Paper | Special Issue on the 2008 International Congress on Advances in Nuclear Power Plants / Thermal Hydraulics | doi.org/10.13182/NT10-A9448
Articles are hosted by Taylor and Francis Online.
This paper describes the heat transfer in intermediate heat exchangers (IHXs) of liquid-metal-cooled fast reactors when the flow rate is low, such as under natural-circulation conditions. Although empirical correlations of heat transfer coefficients for IHXs were derived using test data of the fast reactors Monju and Joyo and of a 50-MW steam generator facility, the measured heat transfer coefficient was very low compared to the well-known correlation for liquid metals proposed by Seban and Shimazaki. The heat conduction (HC) in IHX is discussed as a possible cause of the low Nusselt number. However, the present results show that HC is not significant under natural-circulation conditions, and the HC term in the energy equation can be neglected in the one-dimensional plant dynamics calculation. Simulations relating natural-circulation transients tested at the Monju reactor were conducted using the NETFLOW++ code with the proposed empirical correlations. Good agreement was obtained for long-term behavior.