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Record W2915861369 · doi:10.29252/jafm.73.245.27620

Experimental Evaluation of the Critical Flutter Speed on Wings of Different Aspect Ratio

2017· article· en· W2915861369 on OpenAlexaff
Jean M. Bertrand, Hachimi Fellouah

Bibliographic record

VenueJournal of Applied Fluid Mechanics · 2017
Typearticle
Languageen
FieldEngineering
TopicAeroelasticity and Vibration Control
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsFlutterChord (peer-to-peer)WingWind tunnelPropellerAngle of attackReynolds numberAeroelasticityWind speedAerodynamicsCritical speedMechanicsStructural engineeringPhysicsAcousticsVibrationMeteorologyMarine engineeringEngineeringTurbulenceComputer science

Abstract

fetched live from OpenAlex

In this work, wind tunnel experiments were conducted to evaluate the critical flutter speed of wings for three pertinent flight parameters (i) the aspect ratio (AR), (ii) the angle of attack (AoA), and (iii) the aircraft propeller excitation. Six symmetrical wings (NACA0012 design), of fixed chord length of 80 mm and varied AR from 8.75 to 15, were used for this purpose. These wings were mounted horizontally in the wind tunnel as fixed-free condition. The airflow speed is increased slowly until the wing flutters. The results show that the critical flutter speed decreases when the AR increases. For higher AR, the effect of the AoA on the flutter speed is minimal. However, for low AR, the AoA is vital in delaying the flutter instability of the wing. This critical speed spans low to moderate Reynolds numbers based on the wing chord length (Rec =7×104-2×105) which corresponds to the speed range of High Altitude and Long Endurance (HALE) aircraft. In contrast, for a propeller excitation outside the resonance region of the wing, its effect of the on flutter characteristics is not noticeable.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 head0.026
GPT teacher head0.272
Teacher spread0.246 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

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