Unsteady airfoil flow control via a dynamically deflected trailing-edge flap
Bibliographic record
Abstract
The control of the flow around a harmonically oscillating NACA 0015 airfoil via a dynamically deflected simply-hinged trailing-edge flap was investigated experimentally at a Reynolds number of 2.46 x 105 by using a combination of techniques, including surface pressure measurements, hot-wire wake velocity surveys and particle image velocimetry flowfield measurements. The tests were conducted under deep-stall conditions, with special attention being focused on identifying the changes in the flow structures that led to the observed modified aerodynamic load characteristics, and on the evaluation of the effects of the prescheduled trapezoidal flap motion profile. In addition, light-stall and attached-flow oscillations were also considered, as were static flap deflections and higher harmonic flap motions. The results indicate that a trailing-edge flap imposed an effective camber in the trailing-edge region, and was highly effective in the control of the aerodynamic loads. This was achieved in large part by the manipulation of the lower flap surface pressure distribution via changes to the windward-side flow stream, and was unaffected by the state of the flow above the airfoil. The leading-edge vortex, the predominant flow structure over the airfoil, was only marginally affected in its strength and initiation. The results also revealed that both the flap angle and deflection rate contributed to the above observations, and that the active motion was crucial in preventing the flow separation observed over the lower flap surface for an equivalent static flap, which would have hindered its performance. Furthermore, control was limited to the duration of the flap motion, and, in general, no effect on the flow or aerodynamic loads was observed while the flap was withdrawn to its initial undeflected position. The detailed parametric study showed the characteristics of the flap motion profile to be highly influential on the degree of control. In the application of an optimum flap motion schedule to dynamic stall, the severe nose-down pitching moment decreased by 40%, the performance ratio improved by 30%, and the aerodynamic damping became positive and increased four-fold; this was, however, accompanied by a 20% reduction in the maximum lift.
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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".