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May 31–June 3, 2026
Denver, CO|Sheraton Denver
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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.
Seungsu Yuk, Nam Zin Cho
Nuclear Science and Engineering | Volume 181 | Number 1 | September 2015 | Pages 1-16
Technical Paper | doi.org/10.13182/NSE14-88
Articles are hosted by Taylor and Francis Online.
In this paper, we present two novel approaches to reactor core analysis: (1) whole-core fine-group deterministic transport calculations are accelerated by a partial-current-based coarse-mesh finite-difference (p-CMFD) method, and (2) a whole-core domain is decomposed into nonoverlapping local problems, with local problem transport solutions then embedded within the p-CMFD methodology in a two-level iterative scheme to provide a whole-core transport solution. To solve three-dimensional (3-D) reactor problems, both approaches use the two-dimensional/one-dimensional (2-D/1-D) fusion method as a solution kernel, which employs a 2-D method of characteristics in the radial direction and a 1-D SN-like method in the axial direction. A refinement sensitivity study of a 3-D boiling water reactor assembly problem shows the stability and accuracy of the 2-D/1-D fusion method. We report the results of these two approaches as applied to three whole-core configurations of the C5G7 OECD/NEA 3-D benchmark problem and to a modified C5G7 benchmark problem with explicitly modeled cladding.