Turbulent separations beneath semi-submerged bluff bodies with smooth and rough undersurfaces
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Bibliographic record
Abstract
The spatio-temporal characteristics of turbulent separations beneath semi-submerged bluff bodies with different undersurface roughness conditions are studied using a time-resolved particle image velocimetry. The Reynolds number based on the free-stream velocity and submergence depth was fixed to 14 400. Three different undersurface conditions – smooth, sandpaper roughness and cube roughness – were examined. The results showed that wall roughness reduces the mean reattachment length, and suppresses the Reynolds stresses in the second half of the mean separation bubble. The Kelvin–Helmholtz instability is observed at the leading edge of the smooth bluff body, but is bypassed in the rough cases. In the first half of the mean separation bubble, the frequencies in the separated shear layer migrate to lower values in a discrete manner through the vortex pairing mechanism. Consequently, multiple vortex shedding motions at different frequencies are nested in the separated shear layer, and the cores of shed vortices are aligned near the isopleth of free-stream velocity. The shed vortex is accompanied with multiple vortices along the edge of mean flow reversal in the upstream locations. These vortices are influenced significantly by wall roughness. A low-frequency flapping motion manifests as enlargement/shrinkage of reverse flow areas in the first half of the mean separation bubble. The frequencies of flapping motion in the smooth and sandpaper cases are similar, but are relatively lower than that in the cube roughness case. This flapping motion is associated with an extremely large vortex shed from the mean reattachment point to the free-stream region.
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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 | 0.000 |
| 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) | 0.000 | 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.
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