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Record W2267390824 · doi:10.1115/imece2014-37194

Large Eddy Simulation of Round Impinging Jets With Large Stand-Off Distance

2014· article· en· W2267390824 on OpenAlexafffund
Mehrdad Shademan, Vesselina Roussinova, Ron M. Barron, Ram Balachandar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNozzleMechanicsJet (fluid)TurbulenceVortexWakeLarge eddy simulationPhysicsReynolds numberDeflection (physics)Detached eddy simulationClassical mechanicsReynolds-averaged Navier–Stokes equationsThermodynamics

Abstract

fetched live from OpenAlex

Large Eddy Simulation (LES) has been carried out to study the flow of a turbulent impinging jet with large nozzle height-to-diameter ratio. The dynamic Smagorinsky model was used to simulate the subgrid-scale stresses. The jet exit Reynolds number is 28,000. The study presents a detailed evaluation of the flow characteristics of an impinging jet with nozzle height of 20 diameters above the plate. Results of the mean normalized centerline velocity and wall shear stress show good agreement with previous experiments. Analysis of the flow field shows that vortical structures generated due to the Kelvin-Helmholtz instabilities in the shear flow close to the nozzle undergo break down or merging when moving towards the plate. Unlike impinging jets with small stand-off distance where the ring-like vortices keep their interconnected shape upon reaching the plate, no sign of interconnection was observed on the plate for this large stand-off distance. A large deflection of the jet axis was observed for this type of impinging jet when compared to the cases with small nozzle height-to-diameter ratios.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.222
Teacher spread0.215 · 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
Published2014
Admission routes2
Has abstractyes

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