Comparative Study of Superelastic Ti–Zr–Nb and Commercial VT6 Alloy Billets by QForm Simulation
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Bibliographic record
Abstract
Abstract A comparative simulation of hot radial shear rolling (RSR) of billets made of a superelastic Ti–Zr–Nb and a commercial VT6 alloy was performed using the QForm finite element modeling program. Rolling in 48 modes with a variable feed angle and elongation ratio at 4 levels and initial rolling temperature at 3 levels was investigated for each alloy. The Ti–Zr–Nb alloy rheology during hot deformation was determined experimentally by hot upset forging and imported into the QForm program. The presence of maxima on the flow curves at the initial stage of deformation, which are absent in the VT6 alloy, is revealed. Simulation results are presented in the form of fields of the stiffness coefficient, strain rate intensity, cumulative strain degree in the maximum reduction section depending on the rolling mode. General regularities of the Ti–Zr–Nb and VT6 behavior in RSR are similar. The gradient of the fields studied decreases, and the roll pressure and torque increase with an increase in the feed angle and elongation ratio. The initial rolling temperature does not significantly affect the deformation pattern, but it significantly affects the roll pressure and torque. At the same time, the experimental alloy demonstrated the greater tendency to localize deforming forces in the near-contact zone and to increase the gradient of stress-strain state parameters over the billet section. The study of the tightening shape and depth of rolled billet ends showed that the Ti–Zr–Nb alloy has a 3.5–9.6% greater tightening depth. It is shown that experimental alloy rolling requires 1.6–2.4 times higher roll pressure and torque as compared to the commercial alloy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it