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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.
Nafisah Khan, Lixuan Lu
Nuclear Technology | Volume 172 | Number 3 | December 2010 | Pages 278-286
Technical Paper | Instrumentation and Control Systems | doi.org/10.13182/NT10-A10936
Articles are hosted by Taylor and Francis Online.
This paper presents a decoupling algorithm for a large pressurized heavy water reactor to facilitate the design of a decentralized control system. The reactor models are generally high-order systems, which increases the difficulty of designing control systems. A convenient method of model reduction while maintaining the important dynamic characteristics of the process is through decoupling. The new decoupling algorithm proposed in this paper is used to create a decoupled system for decentralized controller design. To demonstrate the performance of this algorithm, a 72nd-order system was decoupled into three partitions, each containing 20, 27, and 25 states. Both a centralized controller based on the original model and decentralized controllers based on the decoupled model are designed. The advantage of the decentralized controller is shown through a fail-safe study.