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Record W4387534572 · doi:10.1002/cjce.25113

Phase split of <scp>gas–non‐Newtonian</scp> fluid two‐phase flow in a ψ‐shaped branching microchannel

2023· article· en· W4387534572 on OpenAlexvenueno aff
Kai Feng, Gang Yang, Jiaxin Liu, Huichen Zhang

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsPressure dropMechanicsMicrochannelSlug flowTwo-phase flowBifurcationNewtonian fluidMaterials scienceInletBranching (polymer chemistry)BubbleFlow coefficientDrop (telecommunication)Flow (mathematics)ThermodynamicsChemistryComposite materialGeologyPhysicsEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract An experiment of phase split was conducted in a horizontal ψ‐shaped branching microchannel to study the phase distribution and pressure drop at the bifurcation. The pressure drop at the test section and the flow rates of the gas and liquid phases through the three branches were measured. The pressure drop gradients at the inlet and branches were predicted by the correlation based on the separated flow model. The critical condition for the split of the two‐phase flow was determined. The results showed that the gas phase separated from the side arm was more than the liquid phase. A uniform distribution could be achieved for the churn flow in water. Pressure drop occurred at the bifurcation of the side arm under the effect of the vortex in the liquid slug near the bubble nose; the pressure drop was much greater than that at the bifurcation of the run.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.010
GPT teacher head0.235
Teacher spread0.224 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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