Vortex-wake formation and evolution on a prolate spheroid at subcritical Reynolds numbers
Bibliographic record
Abstract
Abstract Three-dimensional (3D) flow reconstruction over a 6:1 prolate spheroid using scanning stereoscopic particle image velocimetry has been conducted in a towing-tank facility. Forces, moments, surface pressure and reconstructed 3D vortical-flow structures are acquired in order to characterize the separated flow within the subcritical regime at three Reynolds numbers (Re = 0.5 × 106, 1.0 × 106 and 1.5 × 106), and at four incidence angles (α = 5◦, 10◦, 15◦ and 20◦). Key flow features are evaluated through the reconstructed 3D flowfield data. In particular, the interaction of the crossflow vortices and the surface-pressure distribution are discussed. It is shown that the crossflow vortices consist of helical vortex tubes as the dominant coherent structures, which are more distinct at large α. For α ≥ 15◦, four high-vorticity regions were observed. A pair of upper vortex tubes, originate on the windward side of the model, while a lower vortex tube is formed on the strong curvature region on the leeward side of the model. The vortex dynamics are further characterized through stretching and tilting terms via the vorticity-transport equation. Larger incidence angles α lead to a stronger alignment of the crossflow vortices with the mean flow direction, which is reflected in the tilting terms. A weak Re dependency of the loads and flow structures within the range 1.0 × 106 ≤ Re ≤ 1.5 × 106 is reported, while a significantly different result was captured for separation at Re = 0.5 × 106. An increase in separation size at Re = 0.5 × 106 at 20◦ results in an additional flow structure; a pair of secondary vortices is formed, leading to a change in the pressure distribution on the model surface when compared to higher Re.
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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 | 0.000 |
| 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) | 0.001 | 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".