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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.
Seungmin Oh, Haijing Gao, Shripad T. Revankar
Nuclear Technology | Volume 158 | Number 2 | May 2007 | Pages 208-218
Technical Paper | Nuclear Reactor Thermal Hydraulics | doi.org/10.13182/NT07-A3836
Articles are hosted by Taylor and Francis Online.
An experimental study and best-estimate thermal-hydraulic code model assessment is performed to investigate the characteristics of the filmwise condensation with and without noncondensable gas in a passive condenser system. A vertical condenser tube is submerged in a water pool, where the heat from the condenser tube is removed through boiling heat transfer. Data are obtained for various inlet steam flow rates and noncondensable gas mass fractions at various system pressure conditions for two tube inner diameters: 26.6 and 52.5 mm. Experimental data are compared with analysis for complete condensation and flow-through conditions. Degradation of the condensation with noncondensable gas is investigated, where the condensation heat transfer coefficient decreases with the noncondensable gas. Experimental results are simulated with the RELAP5 code using two different condensation models. Code predictions are compared with experimental data, and the results indicate that there is a need for improved condensation models in RELAP5.