Separated shear layer transition over an airfoil at a low Reynolds number
Bibliographic record
Abstract
Shear layer development over a NACA 0018 airfoil at a chord Reynolds number of 100 000 was investigated using a combination of flow visualization, velocity field mapping, surface pressure fluctuation measurements, and stability analysis. The results provide a detailed description of shear layer transition on an airfoil at low Reynolds numbers. An extensive comparison of measured surface pressure and velocity fluctuations demonstrated that time-resolved surface pressure sensor arrays can be used to identify the presence of flow separation, estimate the extent of the separated flow region, and measure disturbance growth rate spectra in significantly less time than is required by conventional techniques. Surface pressure sensor measurements of disturbance growth rate, wave number, and convection speed are found to compare well with predictions of linear stability theory, supporting the claim that convection speeds measured in separation bubbles over low Reynolds number airfoils are associated with wave packets of growing disturbances propagating through the shear layer. Through a comparison of measured convection speeds in this investigation and prior low Reynolds number airfoil experiments, it is shown that disturbance convection speeds of between 30% and 50% of the edge velocity are typical for this type of flow, consistent with phase speed estimates from previous analytical studies on transitional separation bubbles. Modal RMS velocity profiles were measured and found to be reasonably predicted by stability theory. The results suggest that, even for the relatively thick NACA 0018 airfoil profile, disturbance development over the majority of the laminar separated shear layer is primarily governed by a linear inviscid mechanism.
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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) | 0.000 | 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".