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Record W3214142054 · doi:10.1063/5.0063049

Spatio-temporal dynamics and disintegration of a fan liquid sheet

2021· article· en· W3214142054 on OpenAlexafffund
Mohsen Broumand, Ali Asgarian, Markus Bussmann, Kinnor Chattopadhyay, Murray J. Thomson

Bibliographic record

VenuePhysics of Fluids · 2021
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsUniversity of TorontoUniversity of New Brunswick
FundersCompute Canada
KeywordsBreakupPhysicsMechanicsSurface tensionBreak-UpSauter mean diameterWeber numberRADIUSOpticsStrouhal numberNozzleTurbulence

Abstract

fetched live from OpenAlex

The dynamic behavior and disintegration mechanisms of a fan liquid sheet in a quiescent atmosphere are investigated over a broad range of differential injection pressures up to Δp≈70 bar through experiments, proper orthogonal decomposition (POD) and spectral analyses, and linear stability analysis (LSA). By fan liquid sheet, we mean a diverging and attenuating liquid stream emanating from a flat fan nozzle with high velocity. High spatiotemporal resolution backlit images reveal the formation-growth-fragmentation process of bag-like structures along the fan liquid sheets, which we predict to be responsible for the overall breakup of the sheets through a mechanism known as “wavy corridor.” Therefore, we propose a conjugate model based on LSA to take into account the role of different shear and surface tension-driven instabilities in defining the liquid sheet intact radius and primary droplet sizes. The predictions of LSA from the dynamic features of the liquid sheets, which mainly depend on the sheet Weber number We, are consistent with the quantitative results obtained from the POD and spectral analyses of the images. While the Strouhal number St and the intact radius R of the fan liquid sheets reduce like We−1/3 with increasing We, the volume median diameter of primary droplets decreases like We−11/12. An image feature consolidation technique along with a machine-learning technique, receiver operating characteristic curve analysis, was used to estimate the mean diameter of spray droplets with a large range of sizes.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.899
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.209
Teacher spread0.202 · 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

Citations13
Published2021
Admission routes2
Has abstractyes

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