Constitutive modelling of aluminium alloy sheet at warm forming temperatures
Bibliographic record
Abstract
The formability of aluminium alloy sheet can be greatly improved by warm forming. However predicting constitutive behaviour under warm forming conditions is a challenge for aluminium alloys due to strong, coupled temperature- and rate-sensitivity. In this work, uniaxial tensile characterization of 0.5 mm thick fully annealed aluminium alloy brazing sheet, widely used in the fabrication of automotive heat exchanger components, is performed at various temperatures (25 to 250 °C) and strain rates (0.002 and 0.02 s-1). In order to capture the observed rate- and temperature-dependent work hardening behaviour, a phenomenological extended-Nadai model and the physically based (i) Bergstrom and (ii) Nes models are considered and compared. It is demonstrated that the Nes model is able to accurately describe the flow stress of AA3003 sheet at different temperatures, strain rates and instantaneous strain rate jumps.
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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 | 0.001 |
| 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".