High strain rate deformation behavior, texture and microstructural evolution, characterization of adiabatic shear bands, and constitutive models in electron beam melted Ti-6Al-4V under dynamic compression loadings
Bibliographic record
Abstract
The results of an investigation on the influence of strain rate on the microstructural and texture evolution, adiabatic shear band characterization, and deformation mechanism of electron beam melted Ti-6Al-4V vertically built cylindrical rods are presented and discussed in this paper. Typical initial microstructure includes a mixture of α (aluminum-rich) and β phases (vanadium-rich) and grain boundary α along with the columnar prior β-grain boundaries. High strain rate compressive loadings were applied using a Split-Hopkinson pressure bar at the strain rates of 700 s−1 and 1650 s−1 at room temperature. By increasing the strain rate from 700 s−1 to 1650 s−1, the maximum stress and total strain in the alloy increased by 510 MPa and 141%, respectively. The higher dislocation density in the more severely deformed sample led to a more considerable amount of dislocation cells and consequent subgrains, high-angle grains, and piled-up dislocations. Intense shear strain localization leading to the adiabatic shear bands formation that occurred at higher strain rates. Texture investigations of the ASB region proposed that α→β phase transformation occurred within the ASB. Flow behavior prediction and experimental data revealed reasonable accordance, using the Gao-Zhang-Yan and the Chang-Asaro model.
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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) | 0.000 | 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".