Dynamic mechanical behavior, microstructure evolution, and restoration mechanism of a β‐Ti alloy during hot compression deformation
Bibliographic record
Abstract
Abstract Metastable β titanium alloys are promising materials for lightweight and energy‐efficient applications due to their high strength and low density. Thermal–mechanical processing (TMP) is one of the most effective ways to improve the mechanical properties of such alloys. This paper describes a systematic TMP investigation on a new metastable β titanium alloy, including its dynamic mechanical behavior, and microstructure evolution, via isothermal compression tests and electron back‐scattered diffraction characterizations. The results show that the compression stress increases with an increase in the strain rate and a decrease in the temperature. After yielding, the compression stress–strain pattern shows flow‐softening behavior at a low temperature and a high strain rate, while sustaining a steady flow state at a high temperature and a low strain rate. The temperature‐rise effect contributes to a large degree of flow softening at high strain rates. After the correction for temperature rise, the stress–strain constitutive relationships are established, showing that the compression behavior varies in different phase regions. Based on the microstructure characterizations, it is found that the dynamic recovery and dynamic recrystallization dominate the hot deformations in β phase region and at low strain rates, while the deformation band as an additional product is found in α + β phase region and at high strain rates. The results contribute to a better understanding of the TMP for the considered alloy and may also represent a useful database for β‐Ti alloy applications in lightweight mechanical systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".