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Record W2583825702 · doi:10.1002/cjce.22804

On the diffusion around a slender drop in a simple shear flow

2017· article· en· W2583825702 on OpenAlexvenueno aff
Moshe Favelukis

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsnot available
FundersShenkar College of Engineering and Design
KeywordsMechanicsPéclet numberCapillary actionDrop (telecommunication)Shear flowStokes flowCapillary numberSimple shearMass transferDimensionless quantityChemistryThermodynamicsFlow (mathematics)Classical mechanicsPhysicsShear stress

Abstract

fetched live from OpenAlex

Abstract Mass transfer around a slender drop in a simple shear and creeping flow, at zero Peclet numbers ( Pe = 0), is the subject of this theoretical report. The problem is governed by two dimensionless parameters: the capillary number ( Ca >> 1) and the viscosity ratio ( λ << 1). The fluid mechanics model of Hinch and Acrivos predicts an S‐shaped drop with pointed ends that is almost parallel with the direction of the flow. Making use of the analogy between electrostatics and diffusion ( Pe = 0), both governed by the Laplace equation, together with the work of Szegö on the capacity of a condenser, a simple model is suggested by assuming the drop to be a slender prolate spheroid with rounded ends. The results suggest the following: (a) as the capillary number increases, the drop becomes thinner and longer and its surface area increases, leading to larger mass transfer rates; and (b) for the same capillary number, extensional flow is much more effective than simple shear flow in mass transfer operations.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.355

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 science0.0010.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.180
Teacher spread0.174 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

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