Extracting dominant three-dimensional coherent structures from timeresolved planar PIV measurements in the wakes of cylindrical bodies
Bibliographic record
Abstract
The present study investigates two techniques for phase averaging time resolved two-dimensional PIV measurements for the purpose of extracting dominant three-dimensional wake characteristics. The first one is the classical phase averaging which uses a reference wake velocity signal measured via Laser Doppler Velocimetry (LDV). The second technique involves obtaining the phase information in each measurement plane using Proper Orthogonal Decomposition (POD) of PIV data and then establishing the relative phase between the planes utilizing the reference LDV signal. These techniques are applied to the results of numerical simulations and experiments on the flow past a circular cylinder immersed in a uniform shear flow. Numerical simulations are completed for ReD = 100 and 300, and experiments are completed for ReD = 2100. The phase-averaged results show that both techniques are able to reconstruct the oblique shedding of dominant spanwise vortices. For the basic case of laminar shedding at ReD = 100, the techniques perform equally well. However, the new POD-based approach is superior when there are temporal variations in the threedimensional wake topology present in the uniform cylinder wake for ReD = 300 and 2100.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".