The development of automated segmentation and quantitative characterization of microtextured regions (MTRs) from the complex heterogeneous microstructures is urgently needed, since MTRs have been proven to be the critical issue that dominates the dwell-fatigue performance of aerospace components. In addition, MTRs in Ti alloys have similarities to microstructures encountered in other materials, including minerals and biomaterials. Meanwhile, machine learning (ML) offers new opportunities. This paper addresses segmentation and quantitative characterization of MTRs, where an ML approach, the Gaussian mixture models (GMMs) coupled with density-based spatial clustering of applications with noise (DBSCAN) clustering algorithms, was employed in order to process the orientation data acquired via EBSD in the Matlab environment. Pixels with orientation information acquired through electron backscatter diffraction (EBSD) are divided and colored into several “classes” (MTRs) within the defined c-axis misorientations (i.e., 25°, 20°, 15°, 10°, and 5°), the precision and efficacy of which are verified by the morphology and pole figure of the segmented MTR. An appropriate range of c-axis misorientations for MTR segmentation was derived, i.e., 15~20°. The contribution of this innovative technique is compared with previous studies. At the same time, the MTRs were statistically characterized in the global region.

The impact of the torsional component on the microstructure and mechanical characteristics of a titanium alloy is examined in this work using a combination of numerical simulation and experimental validation. During the axial closed die rolling (ACDR) forming, the combined effects of compressive and torsional deformation cause a significant increase in the specimen’s cumulative strain. The specimen’s shear strain changes most significantly at the height of H/2. The α-phase has a greater propensity to slip on the conical surface, followed by the cylindrical surface, according to SEM and EBSD analyses. The basal surface has the highest resistance to slip. The formation of a fine isometric α-phase occurs when the compressive component causes the α-phase to become more prone to breakage and fracture. A larger α-phase will form because of the torsional component’s influence, which increases the likelihood that the α-phase will slip and exhibit bending and twisting. With a difference in strength of less than 1 percent and a difference in plasticity between the tangential and radial directions of less than 5 percent, the mechanical properties of the TC11 disks formed by the ACDR show a greater degree of isotropy. The specimens show a tough fracture mode, with radial performance outperforming tangential performance, according to fracture morphology analysis.

The Ti-6242 titanium alloy samples were forged at 1020 °C (slightly above the β-transus) and subjected to ultra-short isothermal holding (0–320 s) prior to quenching to investigate the rapid microstructural evolution in the parent β phase. Electron backscatter diffraction (EBSD) with parent β-phase reconstruction reveals that within only 1–3 s of holding, a pronounced fiber texture develops along the forging axis, superseding the original deformation fiber. This ultrafast texture change is attributed to metadynamic recrystallization (MDRX)—the post-deformation growth of nuclei formed during dynamic deformation. The newly formed -oriented β grains still contain residual substructure, indicating incomplete strain release consistent with MDRX. Longer holds (tens of seconds) lead to more extensive static recrystallization and normal grain growth, which dilute the strong fiber as grains of other orientations form and coarsen. These findings demonstrate that even a brief pause after forging can markedly alter the prior β texture via a MDRX mechanism. This insight highlights a novel approach to microtexture control in Ti-6242: by leveraging MDRX during short holds, one can potentially disrupt the formation of aligned α colony microtextured regions (MTRs, or “macrozones”) upon subsequent cooling, thereby mitigating dwell-fatigue susceptibility. The study revises the interpretation of the recrystallization mechanism in short-term holds and provides guidance for optimizing β-phase processing to improve fatigue performance.