Experimental Test Campaign for Stall Characterization on a Generic Variable Sweep Wing
Bibliographic record
Abstract
Aircraft wing stall is a highly complex phenomenon as several mechanisms interact depending on global and local flow characteristics. Recent developments in numerical methods and aerodynamic modeling make possible the vision of an accurate prediction of stall in the near future. In order to reach this objective, there is a need for a high-quality experimental database for validation, including surface and flowfield measurements. To that purpose, a generic test model was specifically designed and built to provide force balance metrics as well as steady and unsteady pressure signals. In particular, the model takes into account forward, backward, and zero sweep angles while adding high-lift devices in order to modify the stall mechanism on the wing. The model was then tested at the ONERA-F2 wind tunnel, and experimental results validate the model’s intended stall characteristics and provide the needed flow data for future numerical validations. This paper describes the different design choices, the measurement techniques considered for this test campaign, and the first results obtained validating the stall processes expected for the different designed configurations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".