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Record W2898477691 · doi:10.1115/fedsm2018-83495

Comparative Evaluation of Single/Twin Round and Elliptic Jets Using Particle Image Velocimetry

2018· article· en· W2898477691 on OpenAlexaff
Seyed Sobhan Aleyasin, Mark F. Tachie

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsParticle image velocimetryPhysicsMechanicsNozzleJet (fluid)Particle tracking velocimetryVelocimetrySkewnessTurbulenceClassical mechanicsMathematicsThermodynamics

Abstract

fetched live from OpenAlex

Twin round and elliptic jets with nozzle spacing of S/d = 2.8 are investigated and the results are compared with those obtained from single jets. The measurements were performed at Re = 10000 using particle image velocimetry. The results show that the twin elliptic jets merge and combine faster than the round jets. However, the twin elliptic jets have lower spreading than their corresponding single jet but in the round jets it is opposite. The vortical structures obtained using swirling strength analysis are more intense in the elliptic jets compared with the round jets; consistent with their higher spreading. In the shear layers, the velocity skewness is considerably positive due to the diffusion of high-speed jet fluid towards the ambient. On the other hand, the streamwise skewness on the centerline is negative because of the entrainment of low-speed ambient fluid; resulting in centerline velocity decay. In addition, the joint and weighted joint probability density functions are used to understand the dominant events which contribute into the mixing of the jets with their surrounding fluid.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.067
GPT teacher head0.312
Teacher spread0.244 · 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 teacher head, 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

Citations5
Published2018
Admission routes1
Has abstractyes

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