Texture and Mechanical Behavior of Magnesium During Free-End Torsion
Bibliographic record
Abstract
Torsion experiments were carried out on pure magnesium (99.9%) and the magnesium alloy AZ71 under free-end conditions of testing. The alloy had an axisymmetric initial texture, while the pure Mg samples were prepared from a rolled plate with a nonaxisymmetric initial texture. The torque as a function of the twist angle was measured at different temperatures (room temperature, 150°C, and 250°C). During twisting, systematic shortening of the samples was observed (Swift effect). The evolution of the crystallographic texture was analyzed by electron backscattering diffraction measurements. The occurrence of dynamic recrystallization (DRX) was detected in pure Mg at 250°C. The Swift effect in the axisymmetric samples was simulated with the “equilibrium equation” approach using polycrystal modeling. In the nonaxisymmetric samples, the texture was simulated at different angular positions with the help of the viscoplastic self-consistent model. The changes in the textures due to DRX were explained in terms of the Taylor factor. Finally, the texture evolution was interpreted with the help of the behavior of ideal orientations and persistence characteristics of hexagonal crystals in simple shear.
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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 | 0.001 |
| 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) | 0.002 | 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".