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Record W2122451080 · doi:10.1002/cjce.21812

Turbulence effects on the granular model of particle motion in a boundary layer flow

2013· article· en· W2122451080 on OpenAlex
Maziar Dehghan, Hassan Basirat Tabrizi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicParticle Dynamics in Fluid Flows
Canadian institutionsnot available
Fundersnot available
KeywordsTurbulenceMechanicsParticle (ecology)K-epsilon turbulence modelBoundary layerParticulatesK-omega turbulence modelTurbulence kinetic energyFlow (mathematics)PhysicsParticle-laden flowsTurbulence modelingStokes numberTwo-phase flowParticle velocityClassical mechanicsMaterials scienceGeologyChemistryReynolds number

Abstract

fetched live from OpenAlex

Abstract Prediction of particle velocity in a dilute turbulent gas–particle flow nearby a flat solid boundary is investigated numerically using a fully Eulerian two‐fluid model. The particulate phase model is based on the kinetic theory of granular flow. The turbulence in both phases is modelled. Inter‐particle and particle‐wall inelastic collisions are considered. Effects of presence/absence of particulate phase turbulence modelling on velocity of particles are investigated. Results indicate that turbulence modelling is necessary for particulate phase, but conventional models should be modified to consider particulate flow nature. Effects of free stream velocity and particle diameter on turbulence modelling results have been discussed.

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.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.301

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 head0.173
Teacher spread0.165 · 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