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Record W2570851425 · doi:10.1115/1.4035639

Aerodynamics and Vortex Flowfield of a Slender Delta Wing With Apex Flap and Tip Flap

2017· article· en· W2570851425 on OpenAlexaff
T. Lee, L. S. Ko

Bibliographic record

VenueJournal of Fluids Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsMcGill University
Fundersnot available
KeywordsVortexStall (fluid mechanics)Vortex liftMechanicsWingtip vorticesDelta wingFlow visualizationAngle of attackParticle image velocimetryHorseshoe vortexVorticityOpticsWingLift (data mining)Apex (geometry)Materials sciencePhysicsAerodynamicsLift coefficientFlow (mathematics)GeometryMathematicsComputer scienceThermodynamicsReynolds number

Abstract

fetched live from OpenAlex

The effect of apex flap and tip flap, deflected both independently and jointly, on the vortex flow and lift generation of a 65 deg-sweep delta wing was investigated experimentally. The drooped apex flap produced a higher lift at medium-to-high angle of attack regime and also a delayed stall. The anhedral (introduced by the downward tip flap) generally promoted lift increment, whereas dihedral had the opposite effect. Meanwhile, the joint apex and tip flap deflection gave a delayed leading-edge vortex (LEV) breakdown and an enhanced lift. The LEVs were generally drawn closer to the wing upper surface, while being pushed further away from the wing centerline by the application of apex flap and tip flap. The flap also modified the vorticity distribution in the LEV; the bursting behavior was, however, not affected. Dye-injection flow visualization and particle image velocimetry (PIV) measurements of the vortex flow were also discussed.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.732

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.184
Teacher spread0.179 · 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 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

Citations1
Published2017
Admission routes1
Has abstractyes

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