Prediction of flow stresses at high temperatures with artificial neural networks

被引：0
|
作者：
机构：
[1] Wang, L.Y.
[2] Zheng, T.S.
[3] Liu, X.F.
[4] Huang, G.J.
来源：
Wang, L.Y. | 2001年 / Allerton Press Inc.卷 / 11期
关键词：
Backpropagation - High temperature effects - Lithium alloys - Neural networks - Plastic deformation - Plastic flow;
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摘要：
On the basis of the data obtained on Gleeble-1500 Thermal Simulator, the predicting models for the relation between stable flow stress during high temperature plastic deformation and deformation strain, strain rate and temperature for 1420 Al-Li alloy have been developed with BP artificial neural networks method. The results show that the model based on BPNN is practical and it call reflect the actual feature of the deforming process. It indicates that the difference between the actual value and the output of the model is in order of 5%.
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