MétaCan
Menu
Back to cohort
Record W2900516136 · doi:10.1115/1.4041989

Experimental Investigation of Nozzle Spacing Effects on Characteristics of Round Twin Free Jets

2018· article· en· W2900516136 on OpenAlexaff
Andrew Laban, Seyed Sobhan Aleyasin, Mark F. Tachie, Mike Koupriyanov

Bibliographic record

VenueJournal of Fluids Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsNozzleTurbulenceMechanicsParticle image velocimetryReynolds numberReynolds stressTurbulence kinetic energyVorticityJet (fluid)PhysicsShear stressMaterials scienceOpticsVortexThermodynamics

Abstract

fetched live from OpenAlex

The objective of this paper is to investigate the effects of nozzle spacing on the mean velocity and higher-order turbulent statistics of free twin round jets produced from sharp contraction nozzles. The experiments were performed in an air chamber where four nozzle spacing ratios, S/d = 2.8, 4.1, 5.5, and 7.1, were investigated at a fixed Reynolds number of 10,000. A planar particle image velocimetry (PIV) system was used to conduct the velocity measurements. The results show that downstream of the potential core, a reduction in spacing ratio leads to an earlier and more intense interaction between the jets, indicated by enhanced half-velocity width spread rate in the inner shear layers and a significant rise of turbulent intensities and vorticity thickness along the symmetry plane. A reduction in spacing ratio, however, confines the ambient fluid entrainment along the inner shear layers leading to a reduced core jet velocity decay rate. The closer proximity of the jets also leads to the decrease of Reynolds stresses in the inner shear layers but not in the outer shear layers. The Reynolds stress ratios along the jet centerline reveal the highest anisotropy in the potential core region.

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)0.003
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 head0.007
GPT teacher head0.206
Teacher spread0.199 · 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

Citations43
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Fluids EngineeringSame topicAerodynamics and Acoustics in Jet FlowsFrench-language works237,207