Historical Evolution of Thermomechanical Processes Applied to Aluminium Alloys
Bibliographic record
Abstract
Thermo-mechanical processing (TMP), coined 50 years ago for steels to describe combined thermal and mechanical treatments that define both product shape and microstructure/properties, has been practiced since the early industrial revolution. The improved function and control in mechanical shaping equipment were easily adapted to newly discovered aluminum, integrating hot forming, cold deformation and annealing. The TMP goals for Al alloys were grain refinement, substructure preservation, texture control and enhanced precipitation. Hot extrusion became widely employed with exploitation of elongated grains with substructure and strong texture and of press heat treatment (solution during deformation, quenching upon exit). Rolling schedules were tuned to generate desired grain size/shape, substructure and texture. This historical account aims to enhance application of metallography to process optimization and innovation that makes metals more competitive with other materials.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".