A Short Review on Superplasticity of Aluminum Alloys
Bibliographic record
Abstract
Superplastic aluminum (Al) alloys can be used in the forming processes to fabricate complex geometry components for a wide range of applications in the automobile industry, where light weight and high stiffness are needed. Those alloys exhibit extreme tensile elongation of more than 300% at a high homologous temperature and appropriate low strain rate. Superplasticity occurs in Al alloys via the mechanisms of grain boundary sliding, solute drag creep and diffusion creep. Grain boundary sliding usually leads to extensive superplasticity. The activation of grain boundary sliding depends on grain size, strain rate sensitivity, deformation temperature and alloy chemical composition. A complete understanding of influencing factors on Al alloy superplasticity is the key to developing novel superplastic Al alloys. This review discusses the superplastic behavior of several Al alloys, especially focusing on Al-Mg 5xxx alloys. It highlights the mechanisms that govern superplasticity of Al alloys at a low and high strain rate. The factors which influence superplasticity are analyzed. As practice industrial applications, high-cycle-time superplastic forming operations such as quick plastic forming and high-speed blow forming are briefly discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".