Modelling recovery and recrystallisation during annealing of AA 5754 aluminium alloy
Bibliographic record
Abstract
A microstructure model taking into account recovery and recrystallisation has been developed to predict the yield stress and the recrystallised grain size during continuous annealing of cold rolled AA 5754 sheet alloy. Using isothermal annealing tests, recovery and recrystallisation kinetics were quantified as a function of temperature and cold reduction. The model was formulated employing the internal state variable approach with the following three state variables: dislocation density, volume fraction recrystallised, and grain size. A rule of mixtures is adopted to separate the effect of recovery and recrystallisation in the overall softening. Model validation has been carried out by comparing the predicted softening curves with those obtained in continuous heating tests replicating heating rates of industrial continuous annealing lines. The model can be applied to non-isothermal processing routes of industrial cold rolled AA 5754 with thickness reduction in the range 40-80%.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".