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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.
Eduardo A. Villarino, Rudi J. J. Stamm’ler, Aldo A. Ferri, Juan J. Casal
Nuclear Science and Engineering | Volume 112 | Number 1 | September 1992 | Pages 16-31
Technical Paper | doi.org/10.13182/NSE112-16
Articles are hosted by Taylor and Francis Online.
In HELIOS, a two-dimensional program for fuel assembly calculations, the geometric system can be partitioned into heterogeneous space elements. The transport of neutrons and gammas is treated by the CCCP method: current coupling (CC) of the space elements, which are internally treated by collision probabilities (CPs). The region-to-region, region-to-surface, surface-to-region, and surface-to-surface probabilities are evaluated. They are numerically integrated according to Carlvik’s method. It is illustrated that elaborate ray tracing and careful normalization prevent the instabilities that the CPs would otherwise suffer. The angular dependence of the interface currents introduces angular dependence into the last three of these probabilities. A reciprocity relation between region-to-surface and surface-to-region probabilities is derived for the individual angular sectors at the surfaces. Also, a new integral function is introduced, the partial Bickley function. An efficient evaluation method for both normal and partial Bickley functions is presented that reduces the computational time for the CPs by ∼20%.