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Record W2560455985 · doi:10.1115/fedsm2016-7673

Reynolds Number Effects on the Characteristics of Twin Jets Interacting With a Free Surface

2016· article· en· W2560455985 on OpenAlexaff
Mohammad S. Rahman, E. M. Nabess, Mark F. Tachie

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsReynolds numberTurbulenceMechanicsJet (fluid)NozzleBody orificePhysicsParticle image velocimetryFree surfaceThermodynamicsMechanical engineering

Abstract

fetched live from OpenAlex

The effects of Reynolds number on the turbulent characteristics of surface attaching twin jet were investigated experimentally. Particle image velocimetry was used as the velocity measuring technique. Twin jets were produced using square orifice nozzle pair. The Reynolds numbers based on the jet exit velocity and the nozzle width were varied from 2620 to 7900. The offset height ratio was fixed at 2 during the experiments. The jet reattached to the free surface and the reattachment length decreased with increase of Reynolds number. Free surface showed significant effect on the maximum velocity decay, jet spread, streamwise mean velocity distribution, Reynolds shear and normal stresses in the upper jet. The decay and spread rate of the lower jet was comparable to free jet due to less confinement effect. The mean and turbulent quantities reported herein were nearly independent of Reynolds number. Proper orthogonal decomposition was performed to reveal the dynamic role of the energetic structures embedded within 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)0.002
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.005
GPT teacher head0.191
Teacher spread0.187 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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