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Record W2895617529

Self-Excited Oscillations of Wiping Air Knives Part II: Suppression of Jet Oscillation

2018· article· en· W2895617529 on OpenAlexaff
Donal A. Finnerty, Samir Ziada, Joseph R. McDermid

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsMcMaster University
Fundersnot available
KeywordsJet (fluid)PlanarOscillation (cell signaling)Particle image velocimetryMechanicsPhysicsAcousticsJet noiseOpticsTurbulence
DOInot available

Abstract

fetched live from OpenAlex

Planar jets impinging upon a rigid surface exhibit large-scale oscillations and produce high-intensity tonal noise. These phenomena are due to an aeroacoustic feedback mechanism discussed in the first paper in this three paper series. This paper is part of an experimental investigation into the interaction of multiple impinging planar jets. An experimental facility of two auxiliary planar jets placed at an inclined angle either side of a planar impinging jet is used to examine the effect of auxiliary jet velocity on the aeroacoustic feedback mechanism of the centre jet. It is found that auxiliary jets of sufficiently high velocity can eliminate the oscillations of the planar jet. Particle Image Velocimetry (PIV) images and Proper Orthogonal Decomposition (POD) analysis confirm that the auxiliary jets have stabilized the planar jet and eliminated the large vortical structures. Static and dynamic pressure measurements performed in the presence of the auxiliary jets show an increase in the stagnation pressure at the plate along with a reduction in the fluctuating pressure.

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 score0.005

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 communication0.0000.000
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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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
Published2018
Admission routes1
Has abstractyes

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