International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Formulation of the Neural Network for Implicit Constitutive Model (II) : Application to Inelastic Constitutive Equations

  • Lee, Joon-Seong (Dept. of Mechanical System Engineering, Kyonggi University) ;
  • Lee, Eun-Chul (Dept. of Mechanical System Engineering, Kyonggi University) ;
  • Furukawa, Tomonari (Dept. of Mechanical Engineering, The Univ. of New South Wales)
  • Published : 2008.12.01
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Abstract

In this paper, two neural networks as a material model, which are based on the state-space method, have been proposed. One outputs the rates of inelastic strain and material internal variables whereas the outputs of the other are the next state of the inelastic strain and material internal variables. Both the neural networks were trained using input-output data generated from Chaboche's model and successfully converged. The former neural network could reproduce the original stress-strain curve. The neural network also demonstrated its ability of interpolation by generating untrained curve. It was also found that the neural network can extrapolate in close proximity to the training data.

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References

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