Titanium alloy is widely applied in aerospace, medical, shipping and other fields due to its high specific strength and low density. The purpose of this study was to analyze the formability of Ti6Al4V alloys at elevated temperatures. An accurate constitutive model is the basic condition for accurately simulating the plastic forming of materials, and it is an important basis for optimizing the parameters of the hot forging forming process. In this study, the optimization algorithm was used to accurately identify the high-temperature constitutive model parameters of Ti6Al4V titanium alloy, and the hot working diagram was established to optimize the hot forming process parameters. The optimal forming conditions of Ti6Al4V titanium alloy are given. Ti6Al4V alloy was subjected to high-temperature compression tests at 800–1000 °C and at strain rates of 0.01–5 s−1 on a Gleeble-1500D thermal/mechanical simulation machine. Each parameter of the Hansel–Spittel constitutive model was taken as an independent variable, and the accumulated error between the stress calculated by the constitutive model and the stress obtained by experimentation was used as an objective function. Based on response surface methodology, an inverse optimization method for identifying the parameters of the high-temperature constitutive model of Ti6Al4V alloy is proposed in this paper. An orthogonal test design was adopted to obtain sample point data, and a third-order response surface approximate model was established. The genetic algorithm (GA) was applied to reversely optimize the parameters of the constitutive model. To verify the accuracy of the optimized constitutive model, the average absolute relative error (AARE) and correlation coefficient (R) were used to evaluate the reliability of optimized constitutive model. The R value of the model was 0.999, and the AARE value was 0.048, respectively, indicating that the established high-temperature constitutive model for Ti6Al4V alloy has good calculation accuracy. The flow stress behavior of the material could be accurately delineated. Meanwhile, in order to study the formability of Ti6Al4V alloy, the hot processing map of the alloy, based on a dynamic material model, was established in this paper. The optimum hot working domains of the Ti6Al4V alloy were determined within 840–920 °C/0.01–0.049 s−1 and 940–980 °C/0.11–1.65 s−1; the hot processing map was verified in combination with the microstructure, and the fine and equiaxed grains and a large amount of β phase could be found at 850 °C/0.01 s−1.

Microstructure is an important factor that affects the mechanical properties and service life of forgings. Through the full study of the formability of the material, the internal microstructure of the material can be effectively controlled. In order to accurately describe the formability of materials during thermal processing, 3D hot processing maps containing strains were established in this paper, and the 3D hot processing maps were coupled with the finite element method for simulation calculation. The Cr5 alloy steel was subjected to unidirectional thermal compression at a strain rate of 0.005–5 s−1 and temperature range of 900–1200 °C on a Gleeble-1500D thermal simulation machine, in order to obtain the date of true stress and strain. Based on the dynamic material model (DMM), the 3D processing maps of Cr5 alloy steel was established, and the 3D processing maps were associated with the analysis of microstructure evolution during hot deformation. The results show that the optimum thermal deformation conditions are as follows: temperature of 1000–1125 °C, strain rate of 0.01–0.2 s−1, and peak power dissipation of 0.41. The 3D processing maps were coupled with the finite element software FORGE® to simulate the hot working process, and the distribution and change of power dissipation and flow instability domain on the metal deformation under different thermal deformation conditions were obtained. The comparison between the simulation results and metallographic images of typical regions of metal deformation shows that they are in good agreement. This method can effectively predict and analyze the formability of materials during hot processing and provide guidance for practical industrial production.

Warm deformation is a plastic-forming process that differs from traditional cold and hot forming techniques. At the macro level, it can effectively reduce the problem of high deformation resistance in cold deformation and improve the surface decarburization issues during the hot deformation process. Microscopically, it has significant advantages in controlling product structure, refining grain size, and enhancing product mechanical properties. The Gleeble-1500D thermal–mechanical physical simulation system was used to conduct isothermal compression tests on GCr15 bearing steel. The tests were conducted at temperatures of 600–1050 °C and strain rates of 0.01–5 s−1. Based on the experimental data, the critical strain model and dynamic recrystallization model for the warm–hot forming of GCr15 bearing steel were established in this paper. The model accuracy is evaluated using statistical indicators such as the correlation coefficient (R). The dynamic recrystallization model exhibits high predictive accuracy, as indicated by an R-value of 0.986. The established dynamic recrystallization model for GCr15 bearing steel was integrated into the Forge® 3.2 numerical simulation software through secondary program development to simulate the compression process of GCr15 warm–hot forming. The dynamic recrystallization fraction was analyzed in various deformation regions. The grain size of the severe deformation zone, small deformation zone, and difficult deformation zone was compared based on simulated compression specimens under the conditions of 1050 °C and 0.1 s−1 with the corresponding grain size obtained with measurement based on metallographic photos; the relative error between the two is 5.75%. This verifies the accuracy of the established dynamic recrystallization and critical strain models for warm–hot deformation of GCr15 bearing steel. These models provide a theoretical basis for the finite element method analysis and microstructure control of the warm–hot forming process in bearing races.