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Record W2333782948 · doi:10.1061/40655(2002)112

Interfacial Instabilities in Two-Layer Exchange Flow over Smooth Topography

2002· article· en· W2333782948 on OpenAlexaff
Hesham Fouli, Véronique Morin, David Z. Zhu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsParticle image velocimetrySillEntrainment (biomusicology)VelocimetryFlow (mathematics)MechanicsGeologyMaterials sciencePhysicsTurbulenceAcoustics

Abstract

fetched live from OpenAlex

Two-layer exchange flow was modeled in a rectangular channel connecting two reservoirs of water of slightly different densities. A smooth bottom sill was placed within the channel. Kelvin-Helmholtz (K-H) instabilities were generated at the interface of the exchange flow down the sill. Detailed flow measurements were obtained using digital particle image velocimetry (DPIV) for velocity fields, and laser-induced fluorescence (LIF) for interface positions. The measured flow field indicates that K-H instabilities were generated at bulk Richardson number, J, of about 0.07–0.10 with a significantly displaced density field from the center of the shear layer. The generation, growth and propagation of those K-H instabilities were measured from the record of the interface positions. Those instabilities caused significant flow entrainment with the upper layer fluid entrained into the lower layer and the flow rate in the lower layer increasing by about 20% down the sill was found.

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 score0.005
Threshold uncertainty score0.010

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.211
Teacher spread0.197 · 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

Citations1
Published2002
Admission routes1
Has abstractyes

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