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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.
Richard B. Vilim, Humberto E. Garcia
Nuclear Science and Engineering | Volume 125 | Number 3 | March 1997 | Pages 324-336
Technical Paper | doi.org/10.13182/NSE97-A24278
Articles are hosted by Taylor and Francis Online.
Next generation pool-type power plants will require advanced control techniques to meet operational and safety goals. This is the conclusion after conducting control experiments in the Experimental Breeder Reactor II (EBR-II) to demonstrate a supervisory so-called passive control scheme. The proportional-integral-derivative controller in EBR-II did not adequately compensate for disturbances to inlet temperature that occurred during normal power changes. The key to better control is to take into account the stratification and energy interchange mechanisms in the primary pool through which these disturbances feed. A model-based control approach for solving this problem is described. A lumped parameter model of the EBR-II primary pool is developed and validated using experimental data. A disturbance rejection method is then used to design a controller that minimizes the effect of those disturbances that cause poor setpoint tracking. The implementation of the controller and results are given in a companion paper.