Artificial Neural Networks Models for Flow Stress during High Temperature Plastic Deformation of Al-Li Alloy
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TG146.21

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    Abstract:

    Using gained experimental data to develop the models of stable flow stresses at high temperature plastic deformation by statistical methods for alloy materials, precision of the models is poor and at the same time the processes of modeling are complicated with great workload. 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 Network method. The results show that the model on basis of BPNN is practical and it reflects the real feature of the deforming process. It states that the difference between the real value and the output of the model is in order of 5 percent.

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刘雪峰 汪凌云.铝锂合金高温变形流变应力的人工神经网络模型[J].重庆大学学报,2001,24(2):68~71

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  • Received:
  • Revised:June 21,2000
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