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Record W3093853246 · doi:10.1115/1.4048875

Effect of Ground Boundary Condition on Near-Field Wingtip Vortex Flow and Lift-Induced Drag

2020· article· en· W3093853246 on OpenAlexaff
Anan Lu, T. Lee

Bibliographic record

VenueJournal of Fluids Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Fluid Dynamics Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsVortexWingtip vorticesDragPhysicsMechanicsLift-induced dragStarting vortexGround effect (cars)Lift-to-drag ratioHorseshoe vortexLift (data mining)VorticityVortex ringClassical mechanicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract The ground proximity is known to induce an outboard movement and suppression of the wingtip vortices, leading to a reduced lift-induced drag. Depending on the ground boundary condition, a large scatter exists in the published lift-induced drag and vortex trajectory. In this experiment, the ground boundary condition-produced disparity in the vortex strength and induced drag were evaluated. No significant discrepancy appeared for a ground distance or clearance larger than 30% chord. As the stationary ground was further approached, there was the appearance of a corotating ground vortex (GV), originated from the downstream progression of a spanwise ground vortex filament, which added vorticity to the tip vortex, leading to a stronger tip vortex and a larger lift-induced drag compared to the moving ground. For the moving ground, the ground vortex was absent. In close ground proximity, the rollup of the high-pressure fluid flow escaped from the wing's tip always caused the formation of a counter-rotating secondary vortex, which dramatically weakened the tip vortex strength and produced a large induced-drag reduction. The moving ground effect, however, induced a stronger secondary vortex, leading to a smaller lift-induced drag and a larger outboard movement of the tip vortex as compared to the stationary ground effect.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.612
Threshold uncertainty score0.740

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 integrity0.0000.001
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 head0.006
GPT teacher head0.231
Teacher spread0.225 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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