Novel analysis for large strains based on particle image velocimetry
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Bibliographic record
Abstract
Over the last few decades, the particle image velocimetry (PIV) technique has become an interesting tool used to measure displacements in the field of experimental mechanics. This paper presents a procedure to interpret PIV displacements, measured following an Eulerian scheme, with the purpose of providing accumulated displacements, velocities, accelerations, and strains on points representing physical particles. Strains are computed as the gradient of displacements. When compared with other standard procedures already published, the presented methodology is especially well suited to interpret large strains. The basis of the procedure is to map displacement increments measured through PIV analysis on the subset (or patch) centres into numerical particles that are defined as portions of the moving masses whose deformation is analyzed. The implementation of the method is explained in detail, highlighting its simplicity. The procedure can be used as a post-processor of currently available PIV software packages. The methodology is first applied to synthetic cases of rectangular samples in which known displacements are imposed and also to a sandy slope failure experiment involving large displacements. The method reproduces satisfactorily the recorded images.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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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