中國(guó)有色金屬學(xué)報(bào)(英文版)
Transactions of Nonferrous Metals Society of China
| Vol. 11 No. 2 April 2001 |
Artificial neural network model of constitutive relations
for shock-prestrained copper
for shock-prestrained copper
YANG Yang(楊 揚(yáng))， ZHU Yuan-zhi(朱遠(yuǎn)志)， LI Zheng-hua(李正華)，
ZHANG Xin-min(張新明)， YANG Li-bin(楊立斌)， CHEN Zhi-yong(陳志永)
ZHANG Xin-min(張新明)， YANG Li-bin(楊立斌)， CHEN Zhi-yong(陳志永)
（Department of Material Science and Engineering,
Central South University, Changsha 410083, P.R.China）
Abstract:Data from the deformation on Split-Hopkinson Bar were used for constructing an artificial neural network model. When putting the thermodynamic parameters of the metals into the trained network model, the corresponding yielding stress can be predicted. The results show that the systematic error is small when the objective function is 0.5, the number of the nodes in the hidden layer is 6 and the learning rate is about 0.1, and the accuracy of the rate-error is less than 3%.
Key words: shock-prestrain; constitutive relations; artificial neural network model
