Modeling of Constitutive Relationship of Ti600 Alloy Using BP Artificial Neural Network

Abstract:

Isothermal compression deformation tests were conducted for Ti600 alloy column samples by Gleeble-1500 thermal simulator. According to the obtained experimental data (deformation temperatures of 800-1100 oC and strain rates of 0.01-10 s-1), the high temperature constitutive relationship model for the alloy was built based on the BP neural network. Results show that the constitutive relationship model of BP neural network is of high prediction accuracy, which can describe the complicated nonlinear relationship of thermodynamical parameters well. Therefore it provides a more convenient and more effective way to establish the model of constitutive relationship for titanium alloys.