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Record W2094202430 · doi:10.2514/1.17263

Dynamic Stall Flow Control via a Trailing-Edge Flap

2006· article· en· W2094202430 on OpenAlexafffund
P. Gerontakos, T. Lee

Bibliographic record

VenueAIAA Journal · 2006
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStall (fluid mechanics)Trailing edgePitching momentMechanicsDeflection (physics)Leading edgeAirfoilVortexAngle of attackWingMaterials scienceAerodynamicsStructural engineeringPhysicsEngineeringOptics

Abstract

fetched live from OpenAlex

Results of a series of dynamic stall tests in a wind tunnel of an aerofoil fitted with a pitching, trailing edge flap are presented. Phase angle, amplitude, motion profile and duration of the flap wereinvestigated to assess the potential of the flap of mitigating the adverse effects of dynamic stall. The tests were a continuation of the investigations by Feszty et al. (2004) using a computational fluid dynamics method, and the results broadly confirm their conclusions. The results presented in this paper also confirm the observations from experimental work Gerontakos and Lee (2006) and Lee and Gerrontakos (2007) at lower Reynolds number in dynamic stall by strong suction being generated over the aerofoil lower surface, and it is the modification to the lower surface shape by the flap that creates this effect. The dynamic stall vortex acts to enhance the lower surface suction, and careful flap phasing and flap motion profile shaping can make the control more effective.

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)0.000
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.002
GPT teacher head0.171
Teacher spread0.169 · 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

Citations112
Published2006
Admission routes2
Has abstractyes

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