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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.
Man Gyun Na, Dong Won Jung, Sun Mi Lee
Nuclear Science and Engineering | Volume 148 | Number 1 | September 2004 | Pages 153-161
Technical Paper | doi.org/10.13182/NSE04-A2447
Articles are hosted by Taylor and Francis Online.
A receding horizon control method is used to solve on-line, at each time step, an optimization problem for a finite future interval and to implement the first optimal control input as the current control input. The receding horizon control method is combined with a parameter estimator to overcome the problems of the linear modeling and time-varying characteristics of a process. It is a suitable control strategy for time-varying systems, in particular, because the parameter estimator identifies a controller design model recursively at each time step, and also the receding horizon controller recalculates an optimal input at each time step by using newly measured signals. The proposed controller is applied to the axial power distribution control in a pressurized water reactor. The reactor dynamics model used for computer simulations is a two-point xenon oscillation model in which the reactor core is axially divided into two regions (upper and lower halves) and each region is assumed to have a single input and a single output and to be coupled with the other region. It is shown from numerical simulations that the proposed controller exhibits very fast tracking responses due to the step and ramp changes of axial target shape and also works well in a time-varying parameter condition.