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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.
Sung T. Kim, J. J. Doming
Nuclear Science and Engineering | Volume 105 | Number 1 | May 1990 | Pages 16-30
Technical Paper | doi.org/10.13182/NSE90-A19209
Articles are hosted by Taylor and Francis Online.
A new discrete nodal transport method has been developed for general two-dimensional curvilinear geometry by using boundary-fitted coordinate transformation from the general “physical” coordinates to square “computational” coordinates. The metrics that appear in the transformed transport equation are expanded using simple polynomial functions, and the angular divergence term is treated in the same way it is treated in Sn methods for curved geometries. Because the metrics of the transformation depend on the computational coordinates, the technical details of the formal development of the nodal method differ from those of ordinary nodal methods for rectangular geometry. However, the computational process in the transformed rectangular coordinate system is very similar to that used in conventional discrete nodal transport methods. A discrete Sn method has also been developed to solve the boundary-fitted coordinate transformed transport equation. Simple test problems for nonsimple geometries were solved using the zeroth-order (constant-constant) nodal method, the first-order (linear-linear) nodal method, and the Sn method for the same physical and computational grids. The results for the test problems studied showed that, for most performance criteria, the computational efficiency of the zeroth-order nodal method was the highest of the three methods.