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Record W2023683785 · doi:10.1063/1.4758793

Growth and separation of a start-up vortex from a two-dimensional shear layer

2012· article· en· W2023683785 on OpenAlexaff
Pooria Sattari, David E. Rival, Robert J. Martinuzzi, Cameron Tropea

Bibliographic record

VenuePhysics of Fluids · 2012
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Calgary
FundersTechnische Universität DarmstadtCalifornia Institute of Technology
KeywordsVortexPhysicsMechanicsParticle image velocimetryShear (geology)Starting vortexShear flowDimensionless quantityVortex ringClassical mechanicsHorseshoe vortexBoundary layerVortex sheddingCurvatureVorticityReynolds numberTurbulenceGeometryMaterials scienceComposite material

Abstract

fetched live from OpenAlex

The evolution of an isolated line vortex generated by a starting two-dimensional jet is studied experimentally using time-resolved particle image velocimetry. The vortex growth in this current configuration is not linked to any externally imposed length scales or interactions with other vortical structures or walls that could potentially influence vortex growth. A model for the early-stage vortex growth, based on the transport of circulation from the shear layer into the vortex, is proposed and found to agree well with experimental data. The model provides a scaling scheme for vortex growth using shear-layer characteristic velocity and shear-layer thickness. The vortex growth is limited through a gradual separation of the vortex from the feeding shear layer, arising from decreased shear-layer curvature. This phenomenon is linked to a competition between the shear-layer tendency to remain in the streamwise direction and the induced velocity from the vortex on the shear layer. Finally, a dimensionless number representing this competition is introduced, which in turn is able to describe the gradual separation of the vortex from the shear layer.

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: Simulation or modeling · Consensus signal: none
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 communication0.0010.000
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 head0.012
GPT teacher head0.234
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 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

Citations58
Published2012
Admission routes1
Has abstractyes

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