Drag optimisation of a wing equipped with a morphing upper surface
Bibliographic record
Abstract
ABSTRACT The drag coefficient and the laminar-to-turbulent transition for the aerofoil component of a wing model are optimised using an adaptive upper surface with two actuation points. The effects of the new shaped aerofoils on the global drag coefficient of the wing model are also studied. The aerofoil was optimised with an ‘in-house’ genetic algorithm program coupled with a cubic spline aerofoil shape reconstruction and XFoil 6.96 open-source aerodynamic solver. The wing model analysis was performed with the open-source solver XFLR5 and the 3D Panel Method was used for the aerodynamic calculation. The results of the aerofoil optimisation indicate improvements of both the drag coefficient and transition delay of 2% to 4%. These improvements in the aerofoil characteristics affect the global drag of the wing model, reducing it by up to 2%. The analyses were conducted for a single Reynolds number and speed over a range of angles of attack. The same cases will also be used in the experimental testing of the manufactured morphing wing model.
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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) | 0.001 | 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".