The stability of leading-edge vortices to perturbations on samara-inspired rotors: a novel solution for gust resistance
Bibliographic record
Abstract
The stability of leading-edge vortices (LEVs) on a samara-inspired rotor during steady and unsteady gusty incoming flow was investigated experimentally using direct rotational speed measurements, as well as time-resolved particle image velocimetry (PIV). The blades of the samara-inspired rotor were designed to match the tip-speed ratio, the aspect ratio, and the distribution of the effective angle of attack of samara seeds to utilize LEVs similar to samara seeds. The flow around the blades of the samara-inspired rotor was compared to a reference rotor, which possesses a constant spanwise effective angle of attack, to investigate the influence of the samara-like spanwise effective angle-of-attack distribution on LEV stability. Furthermore, the unsteady performance of the samara-inspired rotor was compared to a generic low-inertia rotor that possesses blades with a constant effective angle of attack less than the stall angle. During steady rotation, the samara-inspired rotor exhibited a stably-attached LEV, while the reference rotor demonstrated unstable LEV shedding. Compared to a generic low-inertia rotor, the samara-inspired rotor demonstrated a relatively stable tip-speed ratio ([Formula: see text]) during the gust. Furthermore, the LEV remained stably-attached on the rotor's blades with a constant normalized circulation during the gust. Finally, the analysis of the LEV stability during the gust using the vorticity transport equation suggests that LEV stability is coupled with constant tip-speed ratio during gusts.
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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) | 0.000 | 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 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".