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Record W2223029945 · doi:10.1063/1.4938095

Breakup of capillary jets with different disturbances

2016· article· en· W2223029945 on OpenAlexafffund
N. Moallemi, Ri Li, Kian Mehravaran

Bibliographic record

VenuePhysics of Fluids · 2016
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsMechanicsAmplitudeVibrationBreakupRADIUSDisturbance (geology)NozzleClassical mechanicsAcousticsOptics

Abstract

fetched live from OpenAlex

The disturbance on a capillary jet can be imposed by radius modulation, velocity modulation, or jet vibration. The objective of the study is to understand the equivalence between the three types of disturbances. Theoretical analysis based on the Bernoulli equation for unsteady flows is conducted. It is found that a radius-modulated disturbance is equivalent to a velocity-modulated disturbance with the same wave number if the non-dimensional amplitude of the radius disturbance is 1.5 times that of the velocity disturbance. This is validated by carrying out numerical simulation based on velocity modulation and comparing with the linear theory based on radius modulation. It is also revealed that disturbance generated by a vibrating nozzle with small amplitude is equivalent to velocity disturbance. The non-dimensional amplitude of the equivalent velocity disturbance is a function of non-dimensional vibration amplitude and vibration wave number. The wave number of the velocity disturbance is shown to be twice of the vibration wave number. Validated by experimental observation, if the vibration wave number is less than 0.5, each nozzle vibration cycle generates two droplets. If the vibration wave number is between 0.5 and 1, each vibration cycle generates one droplet.

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)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.006
GPT teacher head0.182
Teacher spread0.176 · 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

Citations45
Published2016
Admission routes2
Has abstractyes

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