Prediction of the Work-Hardening Exponent for 3104 Aluminum Sheets with Different Grain Sizes
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Bibliographic record
Abstract
A practical approach to predict the yield strength and work-hardening exponent (n value) to evaluate the deep-drawing performance of annealed 3104 aluminum sheets is presented in the present work by only measuring and analyzing the grain size of the sheet. The various grain sizes were obtained through the different annealing treatment and then the evolution of the n value under different strains and the yield strength of annealed 3104 aluminum sheet were evaluated. Results showed that the n value and yield strength vary greatly with the grain size. A mathematical model relating grain size d, work-hardening exponent n, target strain ε, and yield strength Rp0.2 was developed in the present work. Within the studied grain size range d (12–29 μm), the n value generally increased with d in a strain-dependent manner, such that n = 0.1875 − 85.03 × exp [ − d / 1.94 ] when the ε was less than 0.5%, but n = 0.3 − 0.15 d − 1 / 2 when the ε was greater than 2%. On the other hand, the n value was found to depend on the target strain ε as n = 0.276 − A 1 × exp [ − e / 1.0435 ] , where A1 varies with d and its value is in the range of 0.132–0.364. In addition, the relationship between Rp0.2 and d followed the Hall-Petch equation ( R p 0.2 = 36.273 + 139.8 × d − 1 / 2 ).
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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) | 0.000 | 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 it