A Simple Approach to Performing Large Strain Cyclic Simple Shear Tests: Methodology and Experimental Results
Bibliographic record
Abstract
Abstract A simple and efficient methodology has been proposed for characterizing the large strain cyclic simple shear behavior of engineering materials. The proposed methodology includes the use of a modified test specimen coupled with a digital image correlation system to measure the evolution of shear strains during cyclic simple shear deformation. The effectiveness and simplicity of the proposed testing procedure for cyclic simple shear testing lie in the fact that it does not require any custom test apparatus or fixtures to conduct cyclic simple shear tests. The proposed test sample for cyclic simple shear testing makes use of conventional tensile machine with standard grips to conduct the tests. Furthermore, the coupling of the digital image correlation system allows for full-field surface strain mapping, enabling measurement of shear strain evolution throughout the cyclic shear deformation, avoiding any complications associated with shear strain measurements using conventional extensometry techniques. The proposed methodology is successfully applied to characterize the large strain cyclic simple shear behavior of extruded aluminum alloy AA6063 in both T4 and T6 tempered conditions. The obtained cyclic simple shear results are further discussed in light of microstructure evolution during cyclic simple shear deformation.
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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 | 0.004 | 0.003 |
| 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 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".