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Record W2555095606 · doi:10.1177/0954410016675893

The effect of stiffness and geometric parameters on the nonlinear aeroelastic performance of high aspect ratio wings

2016· article· en· W2555095606 on OpenAlex
Frederico Afonso, Gabriel Leal, José Vale, Éder Oliveira, Fernando Lau, Afzal Suleman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicAeroelasticity and Vibration Control
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsFlutterAeroelasticityStiffnessWingBending stiffnessInertiaAspect ratio (aeronautics)Structural engineeringTorsion (gastropod)Swept wingNonlinear systemLift (data mining)MechanicsMaterials scienceAerodynamicsEngineeringPhysicsClassical mechanicsComputer scienceComposite material

Abstract

fetched live from OpenAlex

The increase in wing aspect ratio is gaining interest among aircraft designers in conventional and joined-wing configurations due to the higher lift-to-drag ratios and longer ranges. However, current transport aircraft have relatively small aspect ratios due their increased structural stiffness. The more flexible the wing is more prone to higher deflections under the same operating condition, which may result in a geometrical nonlinear behavior. This nonlinear effect can lead to the occurrence of aeroelastic instabilities such as flutter sooner than in an equivalent stiffer wing. In this work, the effect of important stiffness (inertia ratio and torsional stiffness) and geometric (sweep and dihedral angles) design parameters on aeroelastic performance of a rectangular high aspect ratio wing model is assessed. The torsional stiffness was observed to present a higher influence on the flutter speed than the inertia ratio. Here, the decrease of the inertia ratio and the increase of the torsional stiffness results in higher flutter and divergence speeds. With respect to the geometric parameters, it was observed that neither the sweep angle nor the dihedral angle variations caused a substantial influence on the flutter speed, which is mainly supported by the resulting smaller variations in torsion and bending stiffness due to the geometric changes.

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.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.005
GPT teacher head0.176
Teacher spread0.170 · 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