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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.
O. Lupas, D. Beraha
Nuclear Science and Engineering | Volume 104 | Number 1 | January 1990 | Pages 10-25
Technical Paper | doi.org/10.13182/NSE90-A23697
Articles are hosted by Taylor and Francis Online.
A three-dimensional, coarse-mesh, nonlinear, robust core model adapted to the specific requirements of a digital power distribution control system for boiling water reactors (B WRs) is presented. Optimal core power control can be achieved with a coarse power distribution description if the simulation is accurate enough. A two-stage concept is used to make the model both accurate and fast. A unique computation with an exact but slow conventional simulator provides a detailed physical basis for a reference core state. This input data basis, homogenized to larger spatial zones, enables a fast, one energy group simulator with xenon dynamics to compute transients covering the entire range of states that occur during normal operation. Validation tests have shown a large autonomy and good simulation qualities of the core model for several types of transients of interest for normal BWR operation. Its accuracy combined with fast execution, numerical stability, and ease in handling make the core model suitable for use in on-line core surveillance and control systems with real-time predictive capabilities. These same features also qualify it as a fast, quasi-static simulator for prediction of core behavior beyond the scope of digital control.