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Record W3127909523 · doi:10.1002/cjce.24113

Lattice Boltzmann phase field simulations of droplet slicing

2021· article· en· W3127909523 on OpenAlexvenueno aff
Zeying Lu, Fengjiao Liu, Xijian Liu, Lijuan Zhang, Haikuan Yuan, Jie Lu, Jos Derksen

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSlicingLattice Boltzmann methodsDimensionless quantityBuoyancyDrop (telecommunication)MechanicsNeutral buoyancyPhysicsComputer science

Abstract

fetched live from OpenAlex

Abstract We have performed two‐ and three‐dimensional phase field simulations using the lattice‐Boltzmann method of liquid drops rising through a continuous phase liquid under the influence of buoyancy. In their upward motion, the drops encounter a knife that is placed with the purpose of slicing the drops in two. A range of scenarios has been observed when the drop hits the knife and it has been investigated how the type of scenario depends on the dimensionless parameters governing the motion and slicing of the drop: the Eötvös number, the Morton number, and the ratio of the droplet size and the width of the knife. We studied symmetric and asymmetric encounters between drop and knife and kept track of the size distribution of the resulting fragments.

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)0.001
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 score0.395
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.014
GPT teacher head0.240
Teacher spread0.226 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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