Hot Working Defines Thermomechanical Processing (TMP) for Aluminum Alloys and Composites
Bibliographic record
Abstract
TMP of Al alloys includes hot working with dynamic substructures and deformation bands for texture components combined with static recovery or recrystallization as well as cold working altered by annealing. The above processes are separately tailored for solute (Al, Mg), dispersoid (Al-0.7Fe) and precipitation hardening alloys; aging combined with deformation can raise strength or improve fatigue or corrosion resistance. Hot and cold rolling with suitable holding intervals are managed to combine deformation and annealing textures for planar anisotropy or for producing less fibrous grains to avoid delamination corrosion; grains may be severely refined by discontinuous or continuous recrystallization for superplastic sheet. In hot-billet and impact extrusion as an addition to substructure and texture strengthening, the intense heating near the die may be employed for precipitate solution with exit quenching for press heat treatment to T5 temper. Similarly, friction stir surface treatment and welding provide intense hot straining with additional softening as metal is swept behind the pin. In combination with some of the above, forging provides grain and dispersoid fibering oriented for crack retardation; semi solid forming competes with this.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".