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Record W1614673109 · doi:10.3968/5490

The Research and Design of Experimental Prototype in Flapping-Wing Micro-Air-Vehicles

2014· article· en· W1614673109 on OpenAlexvenueno aff
Xiaolei Zhou, Xiaoyi Jin, Xu Yang, Liqiang Zhang

Bibliographic record

VenueAdvances in natural science/Advances in natural sciences · 2014
Typearticle
Languageen
FieldEngineering
TopicBiomimetic flight and propulsion mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsFlappingWingEngineeringWingspanWind tunnelAerodynamicsBionicsMicro air vehicleAerospace engineeringDesign processFlight testMarine engineeringSimulationAutomotive engineeringStructural engineeringComputer science

Abstract

fetched live from OpenAlex

To get first-hand data of test in flapping wing flight, a Flapping-wing Micro-Air-Vehicles experimental prototype was designed. This test prototype was constructed by using the theory of bionics and Micro-Air-Vehicles (MAV) design. Adopts Size-law to determine the initial design parameters; modal analysis to design the structure of the flapping-wings; hirao tail capacity, static stability to design the spoiler and Four-link theory to design the transmission system. With those theory, the test prototype was realized and can flying in the air. The process of prototype design not only provides a useful reference experience for subsequent design in testing prototype, but also provide an experimental platform for the upcoming wind tunnel experiments.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.327
Teacher spread0.305 · 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 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

Citations3
Published2014
Admission routes1
Has abstractyes

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