Abstract

Ti-6Al-4V (TC4) alloy is a (α + β) two-phase titanium alloy and has good process plasticity, superplasticity, and corrosion resistance. It is widely used in the aerospace industry. During the hot working process, the microstructure and deformation behavior affect its mechanical properties. However, most of the current research focuses on the use of metallographic methods and physical modeling methods to characterize and estimate the evolution of microstructures and lacks accuracy. Therefore, in this study, the thermal deformation behavior of TC4 titanium alloy is predicted and the dynamic recrystallization process is visualized through thermal simulation test, metallographic test, particle swarm optimization–backpropagation (PSO–BP) algorithm, and cellular automata (CA) method. The conclusions are as follows: the grain growth of TC4 titanium alloy is relatively uneven during hot compression. The increase in temperature and the decrease in strain rate are favorable to dynamic recrystallization. After hot compression, the grain texture appeared in the microstructure of TC4 titanium alloy, and the type and strength of texture changed with the change in temperature. Based on the PSO–BP algorithm, the rheological behavior of TC4 titanium alloy during hot compression is predicted. Compared with the experimental value, the correlation of the PSO–BP model is 0.9972, and the error is within 10%. Finally, using the PSO–BP algorithm as the input, combined with the CA method and the related theory of dynamic recrystallization, the dynamic recrystallization behavior of TC4 titanium alloy during hot compression is simulated. The electron backscatter diffraction test is used for comparison, and the simulated microstructure is similar to the experimental structure after removing the influence of some defects. The average grain size error is within 10%. It shows that this model can well predict the dynamic recrystallization behavior of TC4 titanium alloy during hot compression.

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