Effect of Hardening Rate on the Bendability and Fracture Response of AA6082 Aluminum Extrusions in the VDA238-100 Tight Radius Bend Test
Bibliographic record
Abstract
Understanding the microstructure–property relationship in aluminum extrusions is crucial to leverage their potential in automotive lightweighting. The sensitivity of the processing history to the microstructure and through-thickness variations poses a major challenge since it leads to strong directionality in plasticity and fracture. Reliable characterization of the mechanical response under relevant stress states is crucial for the development of modeling strategies and performance ranking in alloy design. To this end, tensile and 3-point bend tests were performed for an aluminum extrusion produced on a laboratory-scale extrusion press at Rio Tinto Aluminium. Direct measurements of surface strains during bending using stereoscopic digital image correlation revealed that a larger bend angle in the VDA238-100 test does not necessarily imply a higher fracture strain. The T4 sample tested in the extrusion direction sustained a bend angle of 104° compared to 68° in T6 for the same nominal bend severity (ratio of sheet thickness to punch radius), despite comparable major fracture strains of 0.60 and 0.58, respectively. It is proposed that the work-hardening behavior governs the strain distribution on the outer bend surface. The higher hardening rate in the T4 condition helped distribute deformation in the bend zone more uniformly. This delayed fracture to larger bend angles since strain is accumulated at a lower rate. To assess whether the effect of the hardening behavior is manifest at a microstructural lengthscale, microcomputed tomography (μ-CT) scans were conducted on interrupted bend samples. The distribution and severity of damage in the form of cracks on the outer bend surface were distinct to the temper and thus the hardening rate.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".