A Nuclear Power Plant Expert System Using Artificial Neural Networks

  • Mal rey Lee
  • Hye-Jin Jeong
  • Young Joon Choi
  • Thomas M. Gatton
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)


In this study, ANNs are introduced to act as a bridge between detailed computer codes and compact simulators with an aim to improve the capabilities of compact expert system. The ANNs compensate for the inaccuracies of a compact expert system occurring from simplified governing equations and a reduced number of physical control volumes, and predict the critical parameter usually calculated from the sophisticated computer code. To verify the appli-cability of the proposed methodology, computer simulations are undertaken for loss of flow accidents (LOFA).


Expert System Back Propagation Neural Network Recall Phase Basic Principle Expert System Thermal Hydraulic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mal rey Lee
    • 1
  • Hye-Jin Jeong
    • 1
  • Young Joon Choi
    • 2
  • Thomas M. Gatton
    • 3
  1. 1.School of Electronics & Information EngineeringChonBuk National UniversityJeonJu, ChonBukKorea
  2. 2.Nuclear Safety Regulation DivisionKorea Institute of Nuclear SafetyTaejonSouth Korea
  3. 3.School of Engineering and TechnologyNational UniversityLa JollaUSA

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