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Record W2076124333 · doi:10.1080/14685240802301965

On the phase velocities of the motions in an offset attaching planar jet

2008· article· en· W2076124333 on OpenAlexafffund
Nan Gao, D. Ewing

Bibliographic record

VenueJournal of Turbulence · 2008
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTurbulenceSpectral lineMechanicsPhysicsReynolds numberJet (fluid)Phase velocityOptics

Abstract

fetched live from OpenAlex

An experimental investigation was performed to characterize the phase velocity of different frequency fluctuations in a turbulent offset attaching jet with a Reynolds number of 44 000 and initial offset distance of H j . The velocities were determined from the change in the phase of the cross-spectra of the fluctuating pressure along the wall and the cross-spectra of the fluctuating wall pressure and fluctuating velocity throughout the flow. The results showed there was upstream propagation of the wall pressure fluctuations near the separation point associated with the flapping motion, but the upstream propagation apparent in the correlation coefficient of the pressure was due to higher frequency fluctuations associated with the recirculating flow. The phase velocities determined from the pressure–velocity cross-spectra for the higher frequency motions showed less-frequency dependence and less acceleration than those determined from the pressure cross-spectra. There was also evidence of two velocities for the shear layer motions and a velocity for the lower frequency wall jet motions not apparent in the results from the pressure cross-spectra. Thus, the phase velocities determined from pressure cross-spectra do not fully reflect the velocities of the motions in the flow.

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: Observational · 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
Metaresearch0.0000.001
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)0.0010.000

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 head0.021
GPT teacher head0.248
Teacher spread0.227 · 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

Citations16
Published2008
Admission routes2
Has abstractyes

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