Quench sensitivity of automotive extrusion alloys
Bibliographic record
Abstract
Al-Mg-Si extrusions are widely used in automotive structures and crash management systems. In terms of material properties, a high yield strength is desirable for downgauging combined with superior ductility to accommodate plastic deformation associated with part forming, mechanical joining and crash with minimal cracking. The role of press quench is well recognised and water spray quenching is typically applied. The authors previously established a preferred minimum quench rate of 50°C/sec. However, the size and complexity of recent profile designs, e.g. for battery enclosures, can result in excessive distortion at high quench rates. It is therefore important to understand the material performance trade-offs with sub-optimal quenching. A test program was conducted using a purpose built “quench simulator” to study the effect of quench rates in the forced air to spray regimes for a range of commonly used automotive alloys. Strength and ductility were quantified by tensile and bend testing.
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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 | 0.000 | 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 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".