Research on hot deformation behavior and numerical simulation of microstructure evolution for Ti–6Al–4V alloy

Accurate flow stress data and microstructure evolution mechanisms are essential for designing and optimizing thermal processing technology for a wide range of metal materials. In this paper, the compression experiment of Ti–6Al–4V alloy were carried out by Gleeble-3500 thermal simulation machine under high-temperature conditions. The constitutive model of alloy was established by the PSO-BP neural network based on the corrected flow stress. And the Najafizadeh–Jonas and Cingara–McQueen model were used to establish critical strain model. Then, JMAK equation and AGS model were constructed by the linear regression method. A numerical simulation model was also developed to simulate the hot behavior of titanium alloy. The results indicate that the prediction error of the FE model for predicting DRX volume fraction and AGS is less than 5%. The research results have a good prediction ability for predicting plastic deformation and microstructure in industrial production.