Effect of angle of attack on vortex dynamics in laminar separation bubbles
Bibliographic record
Abstract
The dynamics of coherent structures that develop within laminar separation bubbles over a NACA 0018 airfoil at Rec = 100 000 and Angles of Attack (AOA) of 0°, 5°, 8°, and 10° are investigated experimentally using a high-speed flow visualization technique and vortex tracking via embedded microphones. The results identify vortex shedding within the separation bubble for all the cases investigated. The vortices form upstream of mean transition location and break down in the vicinity of mean reattachment, with irregular vortex merging events detected in the aft portion of the separation bubble. As the mean size of the separation bubble decreases with increasing angle of attack, vortex shedding characteristics also change appreciably, with shedding frequency increasing and characteristic streamwise wavelength decreasing. However, vortex roll up and salient aspects of vortex development take place within approximately the same regions downstream of separation location in terms of percentage of the bubble length. For all the cases examined, significant cycle-to-cycle variability is observed in salient vortex characteristics, being particularly pronounced in the aft portion of the bubble where vortex merging occurs and significant spanwise deformations of vortex filaments are expected. Merging of the shear layer vortices is shown to occur irregularly between the mean transition and reattachment location, with merging events separated by a relatively wide range of shedding cycles. As the angle of attack increases from AOA = 5° to 10°, the fraction of primary vortices involved in merging increases up to about 25%. However, enhancement in vortex merging is also noted at lower AOA where shedding occurs close to the trailing edge, which is speculated to be linked to upstream scattering of periodic pressure fluctuations induced at the trailing edge.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".