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Conference Spotlight
2026 ANS Annual Conference
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.
Richard Sanchez, Simone Santandrea
Nuclear Science and Engineering | Volume 183 | Number 2 | June 2016 | Pages 196-213
Technical Paper | doi.org/10.13182/NSE15-78
Articles are hosted by Taylor and Francis Online.
A conservative linear surface approximation (CLS) has been recently introduced to speed up the method of characteristics in unstructured meshes. In this work, we present an analysis of the convergence of the CLS in unstructured geometries, which shows that, under optimal conditions, the method converges quadratically with the size of the regions, while the classical step characteristics approximation converges linearly. The predicted convergence rates apply only to a homogeneous convex domain with a regular boundary and regular sources and can be viewed as upper bounds for realistic heterogeneous cases. We also analyze the errors induced by the numerical implementation of the step and CLS approximations and show their impact in the final error. Numerical calculations illustrate the convergence rates.