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Record W2094386285 · doi:10.1002/ppsc.200390006

Self Similarity of Cross‐Stream Droplet Momentum Displacement in Dispersed Multiphase Flow

2003· article· en· W2094386285 on OpenAlexaff
M. Milanez, G.F. Naterer, G. Venn, Giles Richardson

Bibliographic record

VenueParticle & Particle Systems Characterization · 2003
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMechanicsMomentum (technical analysis)ScalingSimilarity solutionSimilarity (geometry)DragDisplacement (psychology)Momentum diffusionFlow (mathematics)Eulerian pathDiffusionPhysicsClassical mechanicsTurbulenceThermodynamicsBoundary layerMathematicsGeometryLagrangian

Abstract

fetched live from OpenAlex

Abstract Analytical methods are developed and applied to droplet motion, as it relates to aircraft icing. Impinging droplets largely affect the heat balance at an iced aircraft surface, as well as the final ice shape. In this study, a similarity solution of the Eulerian droplet momentum equation is developed. Droplet motion near a flat plate is investigated with a similarity solution. By using scaling, sensitivity, order of magnitude and similarity methods, a momentum displacement of droplets (or particles) due to the presence of the solid surface is predicted. Self similarity of the droplet profiles is established, such that downstream propagation can be expressed in terms of a single independent coordinate. Limiting trends of momentum/drag induced and Blasius‐diffusion profiles are found to identify the spatial range encompassing the droplet motion. The predicted results are successfully compared against the scaling requirements.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations7
Published2003
Admission routes1
Has abstractyes

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