Characterizing the Constitutive Properties of AA7075 for Hot Forming
Bibliographic record
Abstract
The work presented herein investigates the constitutive properties of AA7075 as it undergoes a hot stamping/die quenching process. Tensile specimens were solutionized inside a heated furnace set to 470°C. Once solutionized, the samples were quenched to an intermediate temperature using a vortex air chiller at a minimum rate of 52°C/s. Tensile tests were conducted at steady state temperatures of 470, 400, 300, 200, 115 and 25°C. This solutionizing and subsequent quenching process replicated the temperature cycle and quench rates representative of a die quenching operation. The results of the tensile test were analyzed with digital imaging correlation using an area reduction approach. The area reduction approach approximated the cross-sectional area of the tensile specimen as it necked. The approach allowed for the true stress-strain response to be calculated well past the initial necking point. The resulting true stress-strain curves showed that the AA7075 samples experienced almost no hardening at 470°C. As steady state temperature decreased, the rate of hardening as well as overall material strength increased. The true stress strain curves were fit to a modified version of the extended Voce constitutive model. The resulting fits can be used in a finite element model to predict the behaviour of an AA7075 blank during a die quenching operation.
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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 | 0.001 | 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".