Yi Meng

In order to study the deformation behavior of 30CrMnSiNi2A high‐strength steel during thermal forming, a series of hot compression experiments are conducted under deformation conditions in the temperature range of 850–1200 °C and true strain rates of 0.1, 0.5, 1, and 10 s ⁻¹ . Based on the experimental data, the modified Johnson–Cook equation is calculated, and then the backpropagation artificial neural network constitutive model (BP‐ANN) is obtained. By comparison, the BP‐ANN has obvious advantages in describing and predicting the flow behavior of the material. The thermal processing map is drawn to delineate the three regions of dynamic recrystallization, dynamic recovery, and instability region, which is combined with the microstructure map to determine the critical value dominated by the occurrence of dynamic recrystallization mechanism and to construct the deformation mechanism map. At a fixed temperature, finite element simulations are carried out sequentially for different strain stages to determine the average grain size of each stage and determine the optimal parameter loading path. It helps to realize the effective control of the microstructure of the material, to obtain the ideal grain refinement effect.

This study systematically elucidates the microstructural evolution laws of AerMet100 steel under different thermal deformation conditions, employing multiscale characterization techniques, including optical microscopy, electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM), to analyze microstructural features. Quantitative analysis focuses on lath martensite width, geometrically necessary dislocation density, kernel average misorientation, and grain orientation spread, revealing the correlations between these parameters and parent phase austenite, thereby providing new insights into the genetic mechanism of microstructure during deformation. Through orientation analysis of deformed microstructures, the nucleation mechanism of recrystallization is investigated; fine microstructural correlations between lath martensite and high‐temperature austenite are established using TEM. A physically based cellular automaton model is developed, which couples dislocation density evolution to simulate recrystallization behavior under multiple thermomechanical processing paths. Its predictive capability is validated by EBSD measurement data of the original austenite. By tracking the evolution of dislocation configurations within cells during discontinuous thermomechanical processes, this study achieves cross‐scale linkage of microstructural evolution across different thermomechanical stages, providing a theoretical framework and simulation tool for microstructural control of ultrahigh‐strength steels under local heating and complex deformation conditions.

The hot deformation behavior of the near-α titanium alloy TA32 (Ti-5.5Al-3.5Sn-3Zr-1Mo-0.5Nb-0.7Ta-0.3Si) was studied by isothermal compression tests. The deformation temperatures ranged from 700 to 950 °C, with strain rates ranging from 0.001 to 1.0 s⁻¹. The stress–strain curves corresponding to different deformation parameters were studied to evaluate the mechanical behavior. A prediction model of peak stress of TA32 titanium alloy in the dual-phase zone was established, utilizing friction-temperature-corrected flow stress. Electron backscatter diffraction (EBSD) and scanning electron microscopy (SEM) were used to examine the influence of deformation parameters on microstructure evolution. The findings reveal that at 950 °C and 0.01 s⁻¹, the recrystallized volume fraction reaches 34.6%, with an average recrystallized grain size measuring 3.03 μm, which is significantly enhanced compared with those at lower deformation temperatures. By examining the softening behavior across different deformation parameters, it was concluded that dynamic recrystallization (DRX) becomes the primary mechanism. The conclusions of this study can provide some reference and guidance for the microstructure evolution of TA32 alloy during the hot deformation process so as to accelerate the design and optimization of deformation process parameters and the development and popularization of a new high-temperature titanium alloy TA32.