Flutter Limitation of Drag Reduction by Elastic Reconfiguration
Bibliographic record
Abstract
Through experiments, we idealise a plant leaf as a flexible, thin, rectangular plate clamped at the midpoint and positioned perpendicular to an airflow. Flexibility of the structure is considered as an advantage at moderate flow speed because it allows drag reduction by elastic reconfiguration, but it can also be at the origin of several flow-induced vibration phenomena at higher flow speeds. A wind tunnel campaign is conducted to identify the limitation to elastic reconfiguration that dynamic instability imposes. Here we show by increasing the flow speed that the flexibility permits a considerable drag reduction by reconfiguration, compared to the rigid case. However, beyond the stability limit, vibrations occur and limit the reconfiguration. This limit is represented by two dimensionless numbers: the mass number, and the Cauchy number. Our results reveal the existence of a critical Cauchy number below which static reconfiguration with drag reduction is possible and above which a dynamic instability with important fluctuating loads is present. The critical dimensionless velocity is dependant on the mass number. Flexibility is related to the critical reduced velocity, and allows defining an optimal flexibility for the structure that leads to a drag reduction by reconfiguration while avoiding dynamic instability. Furthermore, experiments show that our flexible structure can exhibit two vibration modes: symmetric and anti-symmetric, depending on its mass number. Because the system we consider is bluff yet aligned with the flow, it is unclear whether the vibrations are due to a flutter instability or vortex-induced vibration or a combination of both phenomena.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".