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Record W2530757064 · doi:10.1177/0954410016671342

Vortex flow and lift generation of a non-slender reverse delta wing

2016· article· en· W2530757064 on OpenAlexaff
T. Lee, LS Ko

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsMcGill University
Fundersnot available
KeywordsDelta wingVortexVortex liftWingHorseshoe vortexMechanicsWingtip vorticesLift (data mining)Vortex generatorPhysicsParticle image velocimetryStall (fluid mechanics)Flow visualizationVortex sheddingStarting vortexAngle of attackFlow (mathematics)Vortex ringLift coefficientTurbulenceAerodynamicsReynolds numberComputer science

Abstract

fetched live from OpenAlex

The vortex flow and lift force generated by a 50°-sweep non-slender reverse delta wing were investigated via particle image velocimetry, together with flow visualization and force balance measurement, at Re = 11,000. The non-slender reverse delta wing produced a delayed stall but a lower lift compared to its delta wing counterpart. The stalling mechanism was also found to be triggered by the disruption of the multiple spanwise vortex filaments developed over the upper wing surface. The vortex flowfield was, however, characterized by the co-existence of reverse delta wing vortices and multiple shear-layer vortices. The outboard location of the reverse delta wing vortex further implies that the lift force is mainly generated by the wing lower surface while the upper surface acts as a wake generator. The spatial progression of the flow parameters of the vortex generated by the non-slender reverse delta wing as a function of α was 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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 head0.009
GPT teacher head0.186
Teacher spread0.177 · 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
Published2016
Admission routes1
Has abstractyes

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Same venueProceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace EngineeringSame topicFluid Dynamics and Turbulent FlowsFrench-language works237,207