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Record W1819080217 · doi:10.1115/gt2015-43847

Experimental Study of Stream-Wise Vortex Formation on Swept Circular Cylinders in Cross-Flow

2015· article· en· W1819080217 on OpenAlexaff
W. Allan, J. P. Gostelow, Simon Hogg

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsRoyal Military College of Canada
FundersDurham University
KeywordsReynolds numberVortexWind tunnelMechanicsFlow visualizationPhysicsCylinderFlow (mathematics)AirfoilTurbulenceBoundary layerVortex sheddingWater tunnelKármán vortex streetGeometryMathematics

Abstract

fetched live from OpenAlex

A series of experiments has been undertaken on a swept cylinder in cross-flow in the 2m2 open-jet wind-tunnel at Durham University, at a nominal Reynolds Number of 500,000. Boundary layer instability, leading to transition has been attributed to curious sheets of stream-wise vortices on turbomachinery blades and other airfoils. Cylinders in cross-flow can be scaled to model such flows. Empirical analysis of stream-wise vortex pair spacing on cylinders was proposed in 1970 and various researchers have produced experimental data sets at various Reynolds Numbers and sweep ranges. Oil flow visualization was conducted in this work, the goal of which was to fill an important gap in experimental results, a gap of significance to turbine blade designers amongst others. In this test campaign, clear evidence of stream-wise vortices was exposed, the wavelengths of which compared well with the experimental results of others and with theory, although interesting departures were observed at high sweep angles. A physical explanation for the formation of the vortex and pair spacing, particularly at higher sweeps, is proposed.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.020
GPT teacher head0.254
Teacher spread0.234 · 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 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

Citations0
Published2015
Admission routes1
Has abstractyes

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