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Record W3112579259 · doi:10.1063/5.0030291

Theoretical atomization model of a coaxial gas–liquid jet

2020· article· en· W3112579259 on OpenAlexfundno aff
Lijun Yang, Yupeng Gao, Jingxuan Li, Qingfei Fu

Bibliographic record

VenuePhysics of Fluids · 2020
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaNational Science Fund for Distinguished Young ScholarsUniversity of Guelph
KeywordsBreakupPhysicsCoaxialMechanicsSauter mean diameterJet (fluid)WavelengthWeber numberClassical mechanicsRange (aeronautics)AerodynamicsAction (physics)Stability (learning theory)OpticsThermodynamicsTurbulenceAerospace engineeringMechanical engineeringReynolds numberNozzle

Abstract

fetched live from OpenAlex

This paper makes an effort to establish an explicit expression of Sauter Mean Diameter (SMD) based on the stability analysis theory and images of liquid jet surfaces observed in the experiments. It is believed that waves in a certain wavelength range will form liquid tongues on the surface of the liquid jet. Under the action of aerodynamic force, these liquid tongues will finally peel off and breakup into droplets. In this paper, we extend the classical linear stability theory and then obtain the explicit expression of SMD through full-wave integration according to the mass conservation. Based on this breakup model, the results of the derived SMD expression match favorably with the experimental data.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.013
GPT teacher head0.205
Teacher spread0.192 · 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 designTheoretical or conceptual
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

Citations15
Published2020
Admission routes1
Has abstractyes

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