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Record W2048640836 · doi:10.1615/atomizspr.v19.i1.20

NEWTONIAN AND NON-NEWTONIAN SPRAY INTERACTION WITH A HIGH-SPEED MOVING SURFACE

2009· article· en· W2048640836 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

VenueAtomization and Sprays · 2009
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSplashMaterials scienceViscoelasticityNewtonian fluidNon-Newtonian fluidElasticity (physics)Composite materialDrop impactCoatingMechanicsRheologyImpactionThermodynamicsWetting

Abstract

fetched live from OpenAlex

Motivated by the need to improve spray coating transfer efficiencies, results are presented from an experimental investigation into the interaction between an air-blast spray and a high-speed moving surface. Three model elastic liquids of varying polymer molecular weight and three inelastic liquids of varying shear viscosity were used to isolate the effect of elasticity and shear viscosity, respectively, on spray impaction behavior. In addition, an industrial liquid friction modifier, KELTRACK™, for use in the railroad industry, was included in the spray tests. High-speed photography was used to examine spray impingement. Ligaments, formed as a consequence of a liquid's viscoelasticity, were observed impacting the surface for the higher molecular weight elastic liquids. The effect of increasing elasticity was shown to increase spray coating transfer efficiencies; this is attributed to a larger proportion of the sprayed liquid reaching the target surface as well as an increased splash threshold on impact. Observations and recommendations were stated regarding transfer efficiency improvement considerations.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.518

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 head0.004
GPT teacher head0.203
Teacher spread0.199 · 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