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Record W2526976304 · doi:10.11159/htff16.137

Aerodynamic Analysis of a Bioinspired Multilayer Flexible Wing

2016· article· en· W2526976304 on OpenAlexvenueno aff
Csaba Hefler, Tim Marco Corti, Huihe Qiu

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicBiomimetic flight and propulsion mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsAerodynamicsWingAerospace engineeringComputer scienceBiomimeticsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, aerodynamic characterization and performance analysis of a bioinspired multilayer flexible wing are discussed. Our membrane wing that consists of two separate layers can achieve better performance for applications utilizing flapping wing locomotion. This novel wing has two distinct features, the first, a passive shape deformation that is dependent on the direction of the aerodynamic loading on the wing surface, thus can reduce the negative lift of the upstroking wing without a complex mechanism required for active pitching. The other feature is the vortex trap mechanism realized by the separation of the layers at upstroke that results in a large scale vortex above the upstroking wing. This vortex can also generate additional lift by preserving a low pressure core. These features are inspired by the active wing shape control of birds, as well as an unsteady aerodynamic mechanism called clap and fling exhibited by several flying insect species. Such passive shape control on membrane wings could be utilized on micro air vehicles featuring a simple flapping mechanism design to achieve robustness and light weight.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.193
Teacher spread0.187 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2016
Admission routes1
Has abstractyes

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