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Record W2020385474 · doi:10.1080/15502280500387971

Numerical Study of Air-Particle Two-Phase Flows Inside a Powder Coating Booth

2006· article· en· W2020385474 on OpenAlexaff
Zhenan Li, Chao Zhang, Jesse Zhu

Bibliographic record

VenueInternational Journal for Computational Methods in Engineering Science and Mechanics · 2006
Typearticle
Languageen
FieldEngineering
TopicParticle Dynamics in Fluid Flows
Canadian institutionsWestern University
Fundersnot available
KeywordsTurbulenceParticle (ecology)AirflowMechanicsCoatingPhase (matter)Flow (mathematics)Powder coatingMaterials scienceField (mathematics)Particle sizeCFD-DEMComputational fluid dynamicsPhysicsMathematicsEngineeringThermodynamicsComposite materialGeologyChemical engineering

Abstract

fetched live from OpenAlex

This paper reports on a research project that studies the air and particle two-phase flows in an experimental powder coating booth. The airflow field is obtained by solving three-dimensional Navier-Stokes equation with standard κ − ϵ turbulence model. In addition to solving transport equations for the continuous phase (the air), a discrete second phase (the particles) is solved in a Lagrangian frame of reference. The study is carried out under different operating parameters for different powder particle sizes to investigate the effect of those operating parameters and particle size on the performance of the coating process.

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)0.002
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: none
Teacher disagreement score0.241
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.025
GPT teacher head0.379
Teacher spread0.355 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

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