Effect of the Backward-Facing Step Location on the Aerodynamics of a Morphing Wing
Bibliographic record
Abstract
Over the last decade, aircraft morphing technology has drawn a lot of attention in the aerospace community, because it is likely to improve the aerodynamic performance and the versatility of aircraft at different flight regimes. With the fast paced advancements in this field, a parallel stream of research is studying different materials and designs to develop reliable morphing skins. A promising candidate for a viable morphing skin is the sliding skin, where two or more rigid surfaces remain in contact and slide against each other during morphing. The overlapping between each two panels create a backward-facing step on the airfoil surface which has a critical effect on the aerodynamics of the wing. This paper presents a numerical study of the effect of employing a backward-facing step on the suction side of a National Advisory Committee for Aeronautics (NACA) 2412 airfoil at a high Reynolds number of 5.9 × 106. The effects of the step location on the lift coefficient, drag coefficient and critical angle of attack are studied to find a favorable location for the step along the chord-wise direction. Results showed that employing a step on the suction side of the NACA 2412 airfoil can adversely affect the aforementioned aerodynamic properties. A drop of 21.1% in value of the lift coefficient and an increase of 120.8% in the drag coefficient were observed in case of a step located at 25% of the chord length. However, these effects are mitigated by shifting the step location towards the trailing edge. Introducing a step on the airfoil caused the airfoil’s thickness to change, which in turn has affected the transition point of the viscous boundary layer from laminar to turbulent. The location of the step, prior or post the transition point, has a noteworthy effect on the pressure and shear stress distribution, and consequently on the values of the lift and drag coefficients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".