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Record W3159510060 · doi:10.2514/1.j060258

Laminar Separation Bubble Development on a Finite Wing

2021· article· en· W3159510060 on OpenAlexafffund
Connor E. Toppings, John W. Kurelek, Serhiy Yarusevych

Bibliographic record

VenueAIAA Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAirfoilAngle of attackWingLaminar flowMechanicsBubbleFlow separationReynolds numberParticle image velocimetryPhysicsMaterials scienceGeometryMathematicsBoundary layerAerodynamicsTurbulenceThermodynamics

Abstract

fetched live from OpenAlex

This experimental study considers the development of a laminar separation bubble formed over a finite wing and contrasts it with the flow evolution over a two-dimensional airfoil. The experiments were performed on a reference NACA 0018 airfoil model and a finite wing with an aspect ratio of 2.5 at a Reynolds number of 125,000 involving surface pressure and particle image velocimetry measurements. For equivalent effective angles of attack, the results reveal significant differences between the two- and three-dimensional configurations. Specifically, increasing the effective angle of attack causes the separation bubble to shift upstream on the two-dimensional airfoil, whereas its mean position and streamwise extent remain invariant to spanwise changes in the effective angle on the finite wing. Similarly, the dominant shear layer frequency and characteristics of shear layer rollers do not vary appreciably over the wingspan. This suggests that the sectional analogy between the local effective angle on the wing and that on the airfoil is not universally applicable to the wing sections subjected to the formation of laminar separation bubbles. Instead, the spanwise characteristics of the bubble on the wing are well approximated by those obtained on the airfoil at the angle of attack matching the effective angle of the wing root. It should be noted, however, that these findings are exclusive of the regions in the immediate vicinity of the wing tip and/or root, which were not considered in the present investigations.

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 score0.166
Threshold uncertainty score0.326

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 head0.010
GPT teacher head0.220
Teacher spread0.210 · 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

Citations15
Published2021
Admission routes2
Has abstractyes

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