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Record W4301718286 · doi:10.1615/tsfp7.2290

DROPLET TRANSPORT IN HIGH REYNOLDS NUMBER WAKE FLOW

2011· article· en· W4301718286 on OpenAlexaff
Ali Bagherpour, A. Gordon L. Holloway

Bibliographic record

VenueProceeding of Seventh International Symposium on Turbulence and Shear Flow Phenomena · 2011
Typearticle
Languageen
FieldEngineering
TopicParticle Dynamics in Fluid Flows
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsWakeReynolds numberMechanicsTurbulencePhysicsRange (aeronautics)Reynolds-averaged Navier–Stokes equationsStokes numberFlow (mathematics)Classical mechanicsMaterials science

Abstract

fetched live from OpenAlex

This paper describes a study of droplet transport in high Reynolds number turbulent shear flow. A dilute polydisperse droplet spray was introduced into an axisymmetric disk wake with Re ~ 6 × 105. The Reynolds number and droplet sizes used in this study cover a range of Stokes numbers 5 < St < 500 and a mass loading of 10−2. Data was gathered using a Phase Doppler Interferometer capable of measuring droplet size and 3 components of droplet velocity simultaneously. Results are sorted into 5 ranges of Stokes numbers and include wake profiles of droplet concentration, mean droplet velocity, and the dominant components of the droplet velocity fluctuation covariance.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score0.875

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 head0.013
GPT teacher head0.216
Teacher spread0.203 · 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 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
Published2011
Admission routes1
Has abstractyes

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