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Record W2012007995 · doi:10.1002/aic.13737

Elastic liquid jet impaction on a high‐speed moving surface

2012· article· en· W2012007995 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAIChE Journal · 2012
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSplashDeborah numberReynolds numberMechanicsWeber numberNewtonian fluidElasticity (physics)Jet (fluid)Non-Newtonian fluidMaterials sciencePhysicsComposite materialThermodynamicsTurbulence

Abstract

fetched live from OpenAlex

Abstract In the railroad industry a friction‐modifying non‐Newtonian liquid, showing elastic behavior, may be applied to the rail in the form of a liquid jet. The interaction of this elastic liquid jet and the moving surface—specifically whether it splashes or adheres without splash—is important in this industrial application. Twelve different elastic liquids with widely varying relaxation times were tested to isolate the effect of elasticity from other fluid properties. Using high‐speed imaging, the interaction between the impinging jet and the moving surface could be captured and analyzed. Although similar to Newtonian jets, for which the Reynolds number plays a major role, the Deborah number was also salient to the splash of elastic liquids. At the elevated Weber numbers of the testing, the Weber number had a much smaller impact on splash than did the Reynolds or Deborah numbers. The ratio of the surface velocity to the jet velocity has only a small effect on the splash. © 2012 American Institute of Chemical Engineers AIChE J, 2012

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score0.459

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 head0.010
GPT teacher head0.219
Teacher spread0.209 · 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