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Record W2465063803 · doi:10.1063/1.4955101

Sliding Couette flow in a ribbed annulus

2016· article· en· W2465063803 on OpenAlexafffund
H. V. Moradi, J. M. Floryan

Bibliographic record

VenuePhysics of Fluids · 2016
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAnnulus (botany)Reynolds numberMechanicsPhysicsCylinderVortexInstabilityFlow (mathematics)Centrifugal forceClassical mechanicsGeometryTurbulenceMaterials scienceMathematics

Abstract

fetched live from OpenAlex

The flow in an annulus driven by the axial movement of one of the cylinders has been studied. The stationary cylinder has been fitted with axisymmetric ribs resulting in the appearance of the centrifugal-force-driven instability which leads to the formation of axial vortices. The critical stability conditions have been determined for a wide range of geometries of practical interest; these conditions include the critical Reynolds number as well as the best vortex packing. It has been shown that a sufficiently large increase of the ribs’ wavelength leads to a flow stabilization as the flow becomes nearly rectilinear, thus reducing the strength of the centrifugal force field. It has also been demonstrated that a sufficiently large decrease of the ribs’ wavelength similarly results in the flow stabilization as the stream lifts up above the ribs’ peaks and becomes more rectilinear. Reduction of the annulus’ radius leads to qualitatively different flow responses depending on the position of the moving cylinder. The critical Reynolds number is reduced and the range of the ribs’ wave numbers capable of inducing the instability is increased when the outer cylinder drives the flow. The trend is reversed when the inner cylinder drives the flow. Conditions when the ribbed cylinder is unable to induce any instability and, thus, behaves as a hydraulically smooth cylinder have been identified.

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 score0.901
Threshold uncertainty score0.397

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 head0.008
GPT teacher head0.198
Teacher spread0.190 · 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

Citations14
Published2016
Admission routes2
Has abstractyes

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