Flutter Analysis of a Morphing Wing Technology Demonstrator: Numerical Simulation and Wind Tunnel Testinga
Bibliographic record
Abstract
As part of a morphing wing technology project, the flutter analysis of two finite element models and the experimental results of a morphing wing demonstrator equipped with aileron are presented. The finite element models are representing a wing section situated at the tip of the wing; the first model corresponds to a traditional aluminium upper surface skin of constant thickness and the second model corresponds to a composite optimized upper surface skin for morphing capabilities. The two models were analyzed for flutter occurrence and effects on the aeroelastic behaviour of the wing were studied by replacing the aluminium upper surface skin of the wing with a specially developed composite version. The morphing wing model with composite upper surface was manufactured and fitted with three accelerometers to record the amplitudes and frequencies during tests at the subsonic wind tunnel facility at the National Research Council. The results presented showed that no aeroelastic phenomenon occurred at the speeds, angles of attack and aileron deflections studied in the wind tunnel and confirmed the prediction of the flutter analysis on the frequencies and modal displacements.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".