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...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.展开更多
The quest for an internal state variable constitutive model describing metal deformation is reviewed. First, analogy is drawn between a deformation model and the Ideal Gas Law. The use of strain as a variable in defor...The quest for an internal state variable constitutive model describing metal deformation is reviewed. First, analogy is drawn between a deformation model and the Ideal Gas Law. The use of strain as a variable in deformation models is discussed, and whether strain serves as an internal state variable is considered. A simple experiment that demonstrated path dependence in copper is described. The importance of defining appropriate internal state variables for a constitutive law relates to the ability to accurately model temperature and strain-rate dependencies in deformation simulations.展开更多
文摘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.
文摘The quest for an internal state variable constitutive model describing metal deformation is reviewed. First, analogy is drawn between a deformation model and the Ideal Gas Law. The use of strain as a variable in deformation models is discussed, and whether strain serves as an internal state variable is considered. A simple experiment that demonstrated path dependence in copper is described. The importance of defining appropriate internal state variables for a constitutive law relates to the ability to accurately model temperature and strain-rate dependencies in deformation simulations.
