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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.
J. D. Teachman, R. J. Onega
Nuclear Science and Engineering | Volume 83 | Number 1 | January 1983 | Pages 149-161
Technical Paper | doi.org/10.13182/NSE83-A17996
Articles are hosted by Taylor and Francis Online.
A nonlinear model is developed for the xenon-induced flux oscillation problem that occurs in nuclear power plants. The model is based on Galerkin's method of weighted residuals applied to multigroup diffusion theory. A similar linear model is developed by the same methods in order to consider the effects of the nonlinearities of the system. The effects of multi- and single-energy group considerations are also examined. The one- and three-energy group models give substantial differences in results for a 0.25% perturbation in the absorption cross section in various regions of the core. The effect of the number of profiles describing the flux distribution has an effect on the accuracy of the simulation. The minimum number of profiles is one higher than the number of regions into which the reactor is divided for a one-dimensional calculation. The use of additional profiles causes a small increase in the accuracy of the results at the expense of a dramatic increase in computational time.