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Record W3004975183 · doi:10.1063/1.5140473

Eulerian modeling of charge transport in bi-disperse particulate flows due to triboelectrification

2020· article· en· W3004975183 on OpenAlexaff
M. Ray, F. Chowdhury, Andrew Sowinski, Poupak Mehrani, Alberto Passalacqua

Bibliographic record

VenuePhysics of Fluids · 2020
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPhysicsCharge (physics)MechanicsMomentum (technical analysis)AdvectionDiffusionTest particleEulerian pathElectric fieldParticle (ecology)Kinetic energyTriboelectric effectClassical mechanicsThermodynamics

Abstract

fetched live from OpenAlex

An Eulerian model to describe the behavior of electrically charged particles, which considers charge separation and transfer between particles of two separate species, is developed using the kinetic theory of granular flows. A transport equation for the charge of each particle species is obtained, incorporating the effect of the charge–velocity correlation. Closures for the collisional diffusion of charge and for the charge-velocity covariance are obtained. The developed model is applied to steady-state simulations in a one-dimensional domain with no advection, neglecting momentum transport and assuming a constant granular temperature for the solid species. While this is only a preliminary test of the model, which will require further validation, the results show the prediction of bipolar charging when the particles have different sizes, even though they are made of the same material. This phenomenon is analyzed and is shown to be driven by the electric field produced by the charge accumulated on the particles.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.582

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 communication0.0000.000
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 head0.020
GPT teacher head0.216
Teacher spread0.196 · 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 designBench or experimental
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

Citations13
Published2020
Admission routes1
Has abstractyes

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