A New Video Extensometer System for Testing Materials Undergoing Severe Plastic Deformation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Characterization of materials undergoing severe plastic deformation requires the careful measurement of instantaneous sample dimensions throughout testing. For compressive testing, it is insufficient to simply estimate sample diameter from an easily measured height and volume. Not all materials exhibit incompressibility, and friction during testing can lead to a barreled sample with diameter that varies with height. Video extensometry has the potential to greatly improve testing by capturing the full profile of a sample, allowing researchers to account for such effects. Common two-dimensional (2D) video extensometry algorithms require thin, planar samples, as they are unable to account for out-of-plane deformation. They are, therefore, inappropriate for standard compressive tests which use cylindrical samples that exhibit large degrees of out-of-plane deformation. In this paper, a new approach to 2D video extensometry is proposed. By using background subtraction, the profile of a cylindrical sample can be isolated and measured. Calibration experiments show that the proposed system has a 3.1% error on calculating true yield stress—similar to ASTM standard methods for compressive testing. The system is tested against Aluminum 2024-T351 in a series of cold upsetting tests. The results of these tests match very closely with similar tests from the literature. A preliminary finite element model constructed using data from these tests successfully reproduced experimental results. Diameter data from the finite element model undershot, but otherwise closely matched experimental data.
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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 | 0.001 |
| 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 | 0.000 | 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