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Record W1968419134 · doi:10.1115/fedsm2003-45520

Vortex Shedding From Two Surface-Mounted Prismatic Obstacles in Lock-in Regime

2003· article· en· W1968419134 on OpenAlexafffund
Robert J. Martinuzzi, Brian Havel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVortex sheddingFreestreamReynolds numberWakeBoundary layerMechanicsLaminar flowObstaclePhysicsOpticsDisplacement (psychology)VortexGeometryMaterials scienceMathematicsTurbulence

Abstract

fetched live from OpenAlex

Periodic vortex shedding from two surface-mounted cubes, of height H, in tandem arrangement placed in a thin boundary layer is investigated for a spacing 2H using phase-averaged laser Doppler velocimetry measurements. Tests were conducted for a Reynolds number of 22000, based on H and the freestream velocity, and an approximately 0.07H thick laminar boundary layer. For this obstacle spacing, the shedding frequency scales linearly with the obstacle spacing. It is shown that in this lock-in regime, periodic shedding is triggered by the displacement of the vertical flow along the front face of the downstream obstacle and is thus different from that observed for two-dimensional cylinders in uniform streams. The existence of this three-dimensional effect is then used to explain why lock-in cannot be observed for square cylinders in tandem arrangement.

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: 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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.007
GPT teacher head0.227
Teacher spread0.221 · 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

Citations0
Published2003
Admission routes2
Has abstractyes

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