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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.
Hangbok Choi, Do Heon Kim
Nuclear Science and Engineering | Volume 151 | Number 1 | September 2005 | Pages 88-94
Technical Paper | doi.org/10.13182/NSE05-A2531
Articles are hosted by Taylor and Francis Online.
An optimum refueling simulation method was developed for application to a Canada deuterium uranium 713-MW(electric) (CANDU-6) reactor. The objective of the optimization was to maintain the operating range of the zone controller unit (ZCU) water level so that the reference zone power distribution is reproduced following the refueling operation. The zone controller level on the refueling operation was estimated by the generalized perturbation method, which provides sensitivities of the zone power to an individual refueling operation and the zone controller level. By constructing a system equation of the zone power, the zone controller level was obtained, which was used to find the most suitable combination of the refueling channels. The 250-full-power-day refueling simulations showed that the channel and bundle powers are well controlled below the license limits when the ZCU water level remains in the typical operating range.