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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.
Zhaopeng Zhong, Thomas J. Downar, Yunlin Xu, Mark D. DeHart, Kevin T. Clarno
Nuclear Science and Engineering | Volume 158 | Number 3 | March 2008 | Pages 289-298
Technical Note | doi.org/10.13182/NSE06-24TN
Articles are hosted by Taylor and Francis Online.
The coarse-mesh finite difference (CMFD) formulation is applied as an efficient means of acceleration of the heterogeneous whole-core transport calculation. The CMFD formulation enables dynamic homogenization of the cells during the iterative solution process such that the heterogeneous transport solution can be preserved. Dynamic group condensation is also possible with a two-level CMFD formulation involving alternate multigroup and two-group calculations. The two-dimensional discrete ordinates (SN) method is used as the kernel to generate the heterogeneous solution; the CMFD solution provides the SN kernel with much faster convergence of fission and scattering source distributions. In this paper, the two-level CMFD acceleration has been tested using the VENUS-2 two-dimensional whole-core model; it is shown that the number of SN transport sweeps can be reduced by a factor of about 10 while exactly reproducing the original transport solution. The second level of CMFD acceleration is also significant in reducing the computation time. The application of the CMFD formulation in arbitrary geometry demonstrates that CMFD also works well for irregular geometries.