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Record W3004077534 · doi:10.1017/jfm.2020.260

Impulse-driven drop

2020· article· en· W3004077534 on OpenAlexaff
Hamed Habibi, Rouslan Krechetnikov

Bibliographic record

VenueJournal of Fluid Mechanics · 2020
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDrop (telecommunication)MechanicsBreakupDrop impactSurface tensionMaterials scienceImpulse (physics)Weber numberWettingPhysicsClassical mechanicsThermodynamicsComposite materialTurbulenceComputer science

Abstract

fetched live from OpenAlex

Drop deformation and disintegration regimes have been studied in many contexts ranging from an impact on a solid surface or a liquid layer of varying thickness to a liquid drop suspended in air and hit by a propagating aerodynamic shock wave. As a counterpart, deformation and disintegration of an initially static drop of controlled shape and size sitting on an impulsively driven stiff membrane are explored here experimentally. A significant amount of collected experimental data is used to map the possible drop morphological changes along with the transitions between them. In order to elucidate the effects of impulse intensity, viscosity, surface tension and wetting, we measured the crown height and radius in the drop deformation regimes, as well as the drop detachment and breakup times along with probability density functions of the secondary droplets in the drop disintegration regimes. With the goal to convey the physical mechanisms behind these transient responses, the observations are interpreted with phenomenological models, scalings and estimates highlighting the rich multiscale physics of the impulse-driven drop phenomena.

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: none
Teacher disagreement score0.923
Threshold uncertainty score0.412

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 head0.011
GPT teacher head0.188
Teacher spread0.177 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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