Limit Strain Characterization in an Aluminum Die-Quenching Process
Bibliographic record
Abstract
This work examines the nature of the strain distributions and limit stains during die quenching of a 7000-series aluminum alloy sheet. Forming limit experiments using limiting dome height (LDH) specimens were performed under plane-strain loading conditions using a 100 mm hemispherical Nakazima punch. Strains were measured using in situ stereoscopic digital image correlation (DIC). Two forming processing routes were examined: (i) an intermediate quench and form (IQF) processing route in which the LDH coupons were solutionized, quenched to a preset temperature, and isothermally formed and (ii) a die-quench (DQ) process where the LDH coupons were solutionized, and quenched and formed simultaneously with room temperature (RT) tooling under non-isothermal conditions. The DQ processing route was devised to understand the formability of the alloy under practical die-quenching conditions, while the IQF route was meant to understand the influence of temperature on the formability of the material. The DQ processing route exhibited the best formability from a localization standpoint; however, it was found that at deformations in excess of 0.5 major true strain, an orange-peel defect was present. The IQF process with room temperature tooling may be comparable to a W-temper forming operation. For these conditions, significant Portevin-Le-Chatelier (PLC) bands were present and the formability was approximately 75% less than for the DQ process. All formability results are summarized and a discussion of the interpretation of forming limits under the diffuse necking conditions associated with elevated temperature forming is presented.
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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) | 0.000 | 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".