X. Q. Zhang
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Y. H. Peng
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M. Q. Li and X. Y. Ruan( 1)Department of Plasticity Technology
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Shanghai Jiao TOng University
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Shanghai 200030 2)School of Material Science and Engineering
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Northwestern Polytechnical University
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Xi' an 710072
,
China)
金属学报(英文版)
In the present research, artificial artificial networks hare be applied to establish the constitutive rela- tionship model of Ti - 5Al - 2Sn - 2Zr - 4Mo - 4Cr (wt - % ) alloy. In the first stage of the re- search, an isothermal compressive experiment using Thermecmastor - Z hot simulator is studied to ac- quire the flow stress at different deformation temperature,equivalent strain and equivalent strain rate. Then,a feed - forward neural network is trained by using the experimental data.After the training process is finished, the neural networks become a knowledge-based constitutive relationship system. Comparison of the predicted and experimental results results shows that the neural network model has good le- arning precision and good generalization.The neural neural network methods are found to show much better agreement than existing methods with the experiment data, and have the advantage of being able to deal with noisy for or data with strong non - linear reationships. At last, this model can be aused to simulate the flow behavior of Ti - 5Al - 2Sn - 2Zr - 4Mo - 4Ca alloy.
关键词:
titanium alloy
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