Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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MODELLING THE DYNAMICS OF THE LEAD BISMUTH EUTECTIC EXPERIMENTAL ACCELERATOR DRIVEN SYSTEM BY AN INFINITE IMPULSE RESPONSE LOCALLY RECURRENT NEURAL NETWORK

  • Published : 2009.12.31
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Abstract

In this paper, an infinite impulse response locally recurrent neural network (IIR-LRNN) is employed for modelling the dynamics of the Lead Bismuth Eutectic eXperimental Accelerator Driven System (LBE-XADS). The network is trained by recursive back-propagation (RBP) and its ability in estimating transients is tested under various conditions. The results demonstrate the robustness of the locally recurrent scheme in the reconstruction of complex nonlinear dynamic relationships.

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References

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