The role of leading-edge serrations in controlling the flow over owls’ wing
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Bibliographic record
Abstract
We studied the effects of leading-edge serrations on the flow dynamics developed over an owl wing model. Owls are predatory birds. Most owl species are nocturnal, with some active during the day. The nocturnal ones feature stealth capabilities that are partially attributed to their wing microfeatures. One of these microfeatures is small rigid combs (i.e. serrations) aligned at an angle with respect to the incoming flow located at the wings' leading-edge region of the primaries. These serrations are essentially passive flow control devices that enhance some of the owls' flight characteristics, such as aeroacoustics and, potentially, aerodynamics. We performed a comparative study between serrated and non-serrated owl wing models and investigated how the boundary layer over these wings changes in the presence of serrations over a range of angles of attack. Using particle image velocimetry, we measured the mean and turbulent flow characteristics and analyzed the flow patterns within the boundary layer region. Our experimental study suggests that leading-edge serrations modify the boundary layer over the wing at all angles of attack, but not in a similar manner. At low angles of attack (<20°), the serrations amplified the turbulence activity over the wing planform without causing any significant change in the mean flow. At 20° angle of attack, the serrations act to suppress existing turbulence conditions, presumably by causing an earlier separation closer to the leading-edge region, thus enabling the flow to reattach prior to shedding downstream into the wake. Following the pressure Hessian equation, turbulence suppression reduces the pressure fluctuations gradients. This reduction over the wing would weaken, to some extent, the scattering of aerodynamic noise in the near wake 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 | 0.001 |
| 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 it