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Record W2793167603 · doi:10.1017/jfm.2018.180

Experimental investigation of the scaling of vortex wandering in turbulent surroundings

2018· article· en· W2793167603 on OpenAlexaff
Sean Bailey, Steffen Pentelow, Hari C. Ghimire, Bahareh Estejab, Melissa Green, Stavros Tavoularis

Bibliographic record

VenueJournal of Fluid Mechanics · 2018
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsVortexPhysicsTurbulenceVortex ringParticle image velocimetryMechanicsVortex stretchingAmplitudeHorseshoe vortexStarting vortexFlow visualizationClassical mechanicsFlow (mathematics)Optics

Abstract

fetched live from OpenAlex

The wandering of a wing-tip vortex in free-stream turbulence was documented by analysis of multi-probe hot-wire measurements in a wind tunnel and flow visualisation and particle image velocimetry measurements in a water tunnel. An error-minimisation approach was applied to the hot-wire measurements to estimate the time history of the location of the vortex axis, whereas flow visualisation from two orthogonal views permitted the reconstruction of relatively long sections of the vortex axis. The amplitude of the wandering motion was found to scale with the turbulence intensity, the core radius and the vortex turnover time; this amplitude was insensitive to changes in the integral length and time scales of the turbulence. The period of the vortex wandering was distributed in the range between 1 and 10 vortex turnover times. The wavelength of wandering was distributed at a relatively long value, which scaled with the vortex turnover time. The velocity of vortex wandering depended on the vortex turnover time, but also contained an additional contribution that was consistent with motion induced by bending waves. The prevalence of the vortex turnover time as the scale for vortex wandering was interpreted as evidence that vortex-induced straining of the free-stream eddies bounds the interaction time between the two, thus limiting the time available for linear and angular momentum transfer.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.011
GPT teacher head0.211
Teacher spread0.200 · 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 designObservational
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

Citations21
Published2018
Admission routes1
Has abstractyes

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