Separation control on a NACA 0025 Airfoil Wing Using An Array of Synthetic Jets
Bibliographic record
Abstract
An experimental study was conducted to evaluate the effectiveness of a microblower array in controllingflow separation from a NACA 0025 airfoil at low Reynolds numbers. Unlike previous actuators, the microblower array distributed forcing across two rows of circular jets. The airfoil was tested at a post-stall angle of attack of 10◦ and a chord-based Reynolds number of Rec = 100, 000 as the baseline flow condition. This baseline flow exhibited two dominant instabilities: large-scale vortex shedding in the wake of the airfoil and vortex roll-up in the separated shear layer. The effects of forcing parameters, including excitation frequency, momentum coefficient, and chordwise forcing location, were investigated through wind tunnel experiments. The results showed that the microblower array effectively suppressed flow separation when excitationwas applied at modulated frequencies close to the instability frequencies of either the wake or the separated shear layer. This improved the aerodynamic performance by increasing lift and reducing drag. Forcing at the wake instability frequency maximized the lift recovery while forcing at the shear layer instability frequency achieved greater drag reduction. A threshold momentum coefficient, which varied with both forcing frequency and location, was required to initiate flow reattachment and enhance aerodynamic performance. Beyond the threshold value, the increase in lift coefficient eventually reached a plateau, indicating that the control had saturated. Upstream forcing was more effective, requiring a lower momentum coefficient to achieve flow control while also delivering better performance improvements. Analysis of the controlled flow dynamics revealed that the Kelvin–Helmholtz instability was energizedby the forcing, promoting vortex growth that enhanced momentum mixing and deflected the separated shear layer towards the airfoil surface. Low-frequency forcing generated a large vortex that swept across the airfoil, inducing local momentum entrainment from the freestream into the shear layer and leading to unsteady reattachment. In contrast, high-frequency forcing produced a series of smaller vortices in the shear layer, enhancing momentum transport evenly over the airfoil and resulting in quasi-steady reattachment.
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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".