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http://dx.doi.org/10.5391/IJFIS.2008.8.4.264

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)
Publication Information
International Journal of Fuzzy Logic and Intelligent Systems / v.8, no.4, 2008 , pp. 264-269 More about this Journal
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.
Keywords
Multilayer Neural Network; State Space Method; Modern Control Theory; Implicit Constitutive Model;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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