Effects of Flexible Wings in Hover Flight at Fruit Fly Scale
Bibliographic record
Abstract
Fruit flies have flexible wings that deform significantly. To explore the fluid-structure interaction of flexible wings, we use a well-validated Navier-Stokes equation solver, fullycoupled with a structural dynamics solver. A hover flight is considered at a Reynolds number of Re = 100, equivalent to that of fruit flies. The thickness and density of the simulated wing also corresponds to a fruit fly wing. The wing stiffness and motion amplitude are varied to assess their influences on the resulting aerodynamic performance and structural response. Highest lift of 3.3 is obtained at the lowest-amplitude, highest-frequency motion (reduced frequency of 3.0) at the lowest stiffness (frequency ratio of 0.7) wing, although the corresponding power required is also high. Optimal efficiency of 0.6 was achieved for a lower reduced frequency of 0.3 and frequency ratio 0.35. Compared to the previously reported results at water tunnel scale, the aerodynamic characteristics were similar, while the structural response varied significantly. Despite these differences, the time-averaged lift scaled with the shape deformation parameter γ. The resulting flexible wing motion for the most efficient case was closely aligned to the the fruit fly measurements, suggesting that fruit fly flight aims to conserve energy, rather than to generate large forces.
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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".