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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.
R. J. Sheu, A. Y. Chen, Y.-W. H. Liu, S. H. Jiang
Nuclear Science and Engineering | Volume 159 | Number 1 | May 2008 | Pages 23-36
Technical Paper | doi.org/10.13182/NSE159-23
Articles are hosted by Taylor and Francis Online.
In this study, discrete ordinates and Monte Carlo methods were applied to solve the radiation transport problem for a simplified spent fuel storage cask considering fixed neutron and gamma-ray sources. The results were compared, and the causes for their differences were investigated. In addition, a hybrid method based on the Consistent Adjoint Driven Importance Sampling (CADIS) methodology has been adopted to accelerate the Monte Carlo simulations. CADIS utilizes a deterministic adjoint function for variance reduction through source biasing and consistent transport biasing. The problem encountered and its possible solution for applying the source biasing in such a large volume source are described. Compared with the unbiased case, the computational efficiency is improved by a factor of several tens for neutron transport, and the efficiency is increased tremendously by about five orders of magnitude for gamma-ray transport. It has been demonstrated that the biasing scheme applied here is very effective in the shielding calculations for a spent fuel storage cask using the Monte Carlo method.