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Using the Gleeble-1500D thermal simulation machine, and the Ti-6Al-4V titanium alloy was subjected to isothermal compression test under the conditions of deformation temperature of 1023 K–1323 K, strain rate of 0.01 s −1 –10 s −1  and maximum deformation degree of 60% (the true strain is 0.916), and the stress and strain data under different deformation conditions were obtained. Based on the stress and strain data, the Arrhenius model and Back-Propagation Artificial Neural Network (BP-ANN) model were obtained. The results show that the BP-ANN model has higher accuracy than Arrhenius model, its correlation coefficient is as high as 0.99959, and the average absolute relative error is only 3.0935%. The Ti-6Al-4V titanium alloy model can make up for the lack of prediction accuracy of the constitutive model, and can predict the flow stress in all deformation ranges. Finally, the influence of different deformation temperature, deformation rate and deformation amount on microstructure is analyzed.

Constitutive models and microstructure evolution of Ti-6Al-4V alloy during the hot compressive process