Variation of strain rate sensitivity index of a superplastic aluminum alloy in different testing methods
Bibliographic record
Abstract
The strain rate sensitivity index, m-value, is being applied as a common tool to evaluate the impact of the strain rate on the viscoplastic behaviour of materials. The m-value, as a constant number, has been frequently taken into consideration for modeling material behaviour in the numerical simulation of superplastic forming processes. However, the impact of the testing variables on the measured m-values has not been investigated comprehensively. In this study, the m-value for a superplastic grade of an aluminum alloy (i.e., AA5083) has been investigated. The conditions and the parameters that influence the strain rate sensitivity for the material are compared with three different testing methods, i.e., monotonic uniaxial tension test, strain rate jump test and stress relaxation test. All tests were conducted at elevated temperature (470°C) and at strain rates up to 0.1 s−1. The results show that the m-value is not constant and is highly dependent on the applied strain rate, strain level and testing method.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".