Formability limits, damage and fracture mechanisms in AA5182 Al-Mg sheets formed under subzero temperature conditions
Bibliographic record
Abstract
The applicability of in demand lightweight Al-Mg alloys is constrained by limited formability and surface defects caused by the Portevin-Le Chatelier (PLC) effect, which manifests as serrated plastic flow due to dynamic strain aging. This study investigated the formability limits, damage and fracture mechanisms for commercially available AA5182 sheets subjected to tensile and Erichsen punch forming tests under room (293 K) and cryogenic (77 K) conditions, that latter was achieved using a liquid nitrogen reservoir. The sheet fracture strain and flow strength increased by 47% and 91%, respectively, for the subzero conditions compared to the reference 293 K case, the Considère necking criterion was also globally satisfied and surface wrinkling was fully suppressed. Optical and scanning electron microscopy confirmed that PLC suppression under subzero forming prevented unstable interactions with opposing shear planes, allowing for more even strain distributions and sheet thinning near the fracture zone. The subzero major strains on the forming limit diagram increased by 18%, 43% and 27% for uniaxial, plane strain and equiaxial strain paths, respectively, compared to 293 K. The average surface roughness was also reduced from 1.16 µm to 0.23 µm, representing the difference between Class B and Class A surface finish designations.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".