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Nuclear Reactor Modeling in Load Following Operations for Korea Next Generation PWR with Neural Network  

Lee Sang-Kyung (서울대학교 원자핵학과)
Jang Jin-Wook (한국원자력연구소)
Seong Seung-Hwan (한국원자력연구소)
Lee Un-Chul (서울대학교 원자핵학과)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers D / v.54, no.9, 2005 , pp. 567-569 More about this Journal
Abstract
NARX(Nonlinear AutoRegressive with eXogenous input) neural network was used for prediction of nuclear reactor behavior which was influenced by control rods in short-term period and also by the concentration of xenon and boron in long-term period in load following operations. The developed model was designed to predict reactor power, xenon worth and axial offset with different burnup states when control rods and boron were adjusted in load following operations. Data of the Korea Next Generation PWR were collected by ONED94 code. The test results presented exhibit the capability of the NARX neural network model to capture the long term and short term dynamics of the reactor core and the developed model seems to be utilized as a handy tool for the use of a plant simulation.
Keywords
NARX; Neural Network; Load Following Operation; KNGR;
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