MétaCan
Menu
Back to cohort

Interaction of a Particle-Laden Gaseous Jet with a Confined Annular Turbulent Flow

2001· article· en· W2051828681 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueParticle & Particle Systems Characterization · 2001
Typearticle
Languageen
FieldEngineering
TopicParticle Dynamics in Fluid Flows
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTurbulenceMechanicsReynolds stressFlow (mathematics)Reynolds numberParticle (ecology)Jet (fluid)PhysicsMean flowFinite volume methodTwo-phase flowParticle-laden flowsLarge eddy simulationK-epsilon turbulence modelMaterials scienceGeology

Abstract

fetched live from OpenAlex

A numerical analysis of polydispersed glass particles interacting with a confined turbulent bluff-body flow was performed by combining the finite-volume method for the gaseous flow with a mesh-free Lagrangian approach for the particulate flow. Three turbulence-closure models, namely the Reynolds-stress, the standard k-ϵ, and the nonlinear k-ϵ models, were first comparatively studied for the single-phase flow. The second-moment Reynolds-stress model was then selected for the prediction of the turbulent gaseous flow in a gas-particle system, where an improved eddy-interaction model was used to predict turbulence-induced particle dispersion. The interaction between the two phases was accounted for through coupling source terms. Numerical predictions of two-phase mean and fluctuating velocities for particle sizes ranging from 15 to 115 μm were compared with corresponding experimental data. Reasonably good agreement was achieved for the mean properties of both the gaseous and particulate flows.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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