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Record W4392908534 · doi:10.32920/25412578

Effects of Wing Flexibility on Vortex Behaviors and Aerodynamic Performance in Various Flapping Flights

2024· preprint· en· W4392908534 on OpenAlexaff
YeongGyun Ryu

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicBiomimetic flight and propulsion mechanisms
Canadian institutionsToronto Metropolitan University
FundersKorea Aerospace University
KeywordsFlappingWingWing twistLeading edgeWingtip vorticesVortexAerodynamicsLift (data mining)DownwashAerospace engineeringStructural engineeringHorseshoe vortexEngineeringAerodynamic forceAngle of attackPhysicsMechanicsComputer scienceVortex ring

Abstract

fetched live from OpenAlex

This dissertation presents various studies on vortex structures and aerodynamic characteristics in flapping flexible wings to offer design considerations for flapping micro aerial vehicle (FMAV) developments. A dynamically scaled-up flapping robot, mounted with a6-axis sensor, and a digital particle image velocimetry (DPIV) technique are used to measure aerodynamic force/moment and flow vector-fields during flapping wings in a water tank. Wing models with or without leading edge veins have different thicknesses, providing various wing flexibilities. Studies of flapping wings without veins in two different flapping kinematics are firstly proposed to demonstrate the wing flexibility effect on aerodynamic performance. The flexible wings generally lead to a leading-edge vortex (LEV) generation delay, causing a lift decline. However, the flexible wing in the specific range of flexibility (non-dimensional spanwise flexural stiffness of 35−80) enhances more lift than the rigid and highly flexible wings due to a wider LEV attachment area. The appropriate deformations lead to the attached LEV during the wing reversal. After the stroke reversal, the portion of the attached LEV flows over the leading-edge, causing a downward flux over a new LEV structure near the wingtip. In addition, flexible wings with leading-edge veins had a dynamic camber, causing a poor lift enhancement except for its initial augmentation. Nevertheless, the specific flexible wing (non-dimensional chordwise flexural stiffness of ~1) obtains a higher aerodynamic performance due to reducing the mechanical power requirement to fly. The above LEV attachment is influenced by the downwash from the wingtip vortex (TV). The TV is differed depending on the wingtip shape and the wing deformations, conducting a comparative study of hawkmoth-like and rectangular wings. In a rigid case, the rectangular wing has better aerodynamic performance than the hawkmoth-like wing, whereas in a flexible case, it has not. The flexible hawkmoth-like wing secures a wider LEV region with improved circulations, achieving about twice the increase rate from rigid to flexible wings on lift-drag ratio and a much more lift-power ratio. The results obtained will provide the specific range of wing flexibility and the importance of the wingtip design to allow better aerodynamic performance in FMAV developments with flexible wings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.217
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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