MétaCan
Menu
Back to cohort
Record W3169324854 · doi:10.2514/1.j060337

Full-Span Topology of Trailing-Edge Separation at Different Angles of Attack

2021· article· en· W3169324854 on OpenAlexaff
Sen Wang, Sina Ghaemi

Bibliographic record

VenueAIAA Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsStall (fluid mechanics)Angle of attackReynolds numberVortexParticle image velocimetryMechanicsLeading edgeFlow separationTrailing edgePhysicsWind tunnelWingGeometryBoundary layerTopology (electrical circuits)AerodynamicsTurbulenceMathematics

Abstract

fetched live from OpenAlex

The velocity field over a two-dimensional wing at Reynolds number of 672,000 was investigated to characterize the three-dimensional topology and evolution of the separate flow with variation of the angle of attack. Planar particle image velocimetry over the full span of the wing demonstrated that with increasing angle of attack, isolated pockets of backflow, which appeared near the trailing edge, merged and formed an asymmetric stall cell at angle of attack of 9.7°. The asymmetry was mainly associated with the dissimilar boundary layers developed on the wind tunnel walls at the spanwise ends of the wing. Secondary structures were also observed between the stall cell and the spanwise end. The stall cell topology was characterized using large-scale three-dimensional particle tracking velocimetry measurements using helium-filled soap bubbles. The results showed that the separation bubble had a small wall-normal height with two wall-normal counter-rotating vortices extended up to the edge of the separation bubble. In addition, the investigations demonstrated that vortex generators can induce a symmetric stall cell by removing the secondary structures and isolating the stall cell from the flows at the spanwise ends.

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 score0.553
Threshold uncertainty score0.381

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 head0.014
GPT teacher head0.250
Teacher spread0.236 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAIAA JournalSame topicFluid Dynamics and Turbulent FlowsFrench-language works237,207