Separation Control on an NACA 0025 Airfoil Using an Array of MEMS-Based Synthetic Jets
Bibliographic record
Abstract
Abstract An novel array of micro-electromechanical systems (MEMS) synthetic jets was designed to control flow separation by periodic blowing at two pre-determined frequencies on a NACA 0025 airfoil for a chord Reynolds number Rec = 105 and angle-of-attach α = 10°. The synthetic jets were generated by commercially available microblowers, providing ease of maintenance compared to other customized synthetic jet actuators. The velocity output of this jet array was characterized with hot-wire anemometry (HWA), and reattached flow was identified using smoke-wire visualization. Pressure measurements show that the array can suppress flow separation on the airfoil, resulting in 2.5 times lift recovery. From wake measurements, up to 50% drag reduction was achieved with the actuation of the jet array compared to the baseline (uncontrolled) case. Particle image velocimetry (PIV) was used to visualize the flow fields of the baseline case and two controlled cases. There was a significant difference in the scale of the vortices produced by the jet array and features of the reattached flow between the two actuation frequencies used.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".