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Record W3019997587 · doi:10.1115/etce2001-17068

Computation of Turbulent Gas-Particle Flows Behind a Bluffbody

2001· article· en· W3019997587 on OpenAlexaff
X.-Q. Chen, Metin Renksizbulut, X. Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicParticle Dynamics in Fluid Flows
Canadian institutionsUniversity of WaterlooOntario Power Generation
Fundersnot available
KeywordsTurbulenceMechanicsReynolds stressParticle (ecology)Flow (mathematics)Finite volume methodLarge eddy simulationPhysicsParticle-laden flowsComputationReynolds numberTwo-phase flowParticulatesMoment (physics)Dispersion (optics)Materials scienceClassical mechanicsChemistryMathematicsGeologyOptics

Abstract

fetched live from OpenAlex

Abstract A numerical analysis of multisized glass particles interacting with a confined bluffbody flow was performed by combining the finite-volume method for the gaseous flow with the Lagrangian approach for the particulate flow. The second-moment Reynolds-stress model was used to predict 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 in terms of coupling sources. Numerical predictions of two-phase mean and fluctuating velocities for different particle sizes 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.

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)0.001
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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.233
Teacher spread0.221 · 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

Citations0
Published2001
Admission routes1
Has abstractyes

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