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Record W2089762925 · doi:10.1115/1.4029672

Concurrent Droplet Coalescence and Solidification on Surfaces With Various Wettabilities

2015· article· en· W2089762925 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Fluids Engineering · 2015
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsConcordia University
Fundersnot available
KeywordsCoalescence (physics)IcingMaterials scienceAirflowShear (geology)MechanicsShear flowSolid surfaceWeber numberNanotechnologyComposite materialMechanical engineeringMeteorologyChemical physicsChemistryPhysicsTurbulenceEngineeringReynolds number

Abstract

fetched live from OpenAlex

An experimental study is performed to analyze the shear driven droplet shedding on cold substrates with different airflow speeds typical of those in the flight conditions. Understanding the mechanism of simultaneous droplet shedding, coalescence, and solidification is crucial to devise solutions for mitigating aircraft in-flight icing. To mimic this scenario, the experimental setup is designed to generate shear flow as high as 90 m/s. The droplet shedding at high-speed is investigated on a cold surface (0 and −5 °C) of different wettabilities ranging from hydrophilic to superhydrophobic. Result analyses indicate that on a hydrophilic substrate, the droplets form a rivulet, which then freezes on the cold plate. In contrast, on the superhydrophobic surface, there is no rivulet formation. Instead, droplets roll over the substrate and detach from it under the effect of high shear flow.

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.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.026
GPT teacher head0.232
Teacher spread0.206 · 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