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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.
Chaung Lin, Shyurng-Rern Chang
Nuclear Science and Engineering | Volume 107 | Number 2 | February 1991 | Pages 158-172
Technical Paper | doi.org/10.13182/NSE91-A15729
Articles are hosted by Taylor and Francis Online.
An adaptive predictive control system (APCS) is applied to the design of the recirculation and feedwater control systems of a boiling water reactor. The APCS uses the dead zone method to modify the adaptive law; thus, it is stable in the presence of unmodeled dynamics and bounded disturbances. Two single-input/single-output control systems are used instead of a multi-input/multi-output control system in order to simplify parameter adaptation. The interactions among the subsystems are treated as unmeasured disturbances. A simulation using the reactor model shows that the dome pressure versus recirculation pump speed subsystem is a nonminimum-phase system. To handle this system, the weighting polynomials for the system input and output are incorporated to form an augmented minimum-phase system and then the augmented system is controlled. The proposed algorithm is stable, does not require persistent excitation of the reference input, and performs well, which makes it practical for implementation.