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On the termination of an emerging droplet from a capillary tube over a flat surface by a wetting slug: A one-dimensional quasistatic model and CFD analysis

2024· article· en· W4402828681 on OpenAlexaff
Amgad Salama, Mohamed Zoubeik, Jisheng Kou

Bibliographic record

VenueInternational Journal of Multiphase Flow · 2024
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsQuasistatic processWettingMechanicsSlugCapillary actionTube (container)Computational fluid dynamicsMaterials scienceSurface (topology)GeologyPhysicsThermodynamicsGeometryComposite materialMathematics

Abstract

fetched live from OpenAlex

• A quasistatic modeling approach has been developed to model the dislodgment of a nonwetting droplet by a wetting slug. • A CFD analysis has been developed to provide a framework for validation of the developed model. • Very good match is obtained between the developed model and the CFD work, which builds confidence of the modelling approach. • Snapshots of the progression of the emergence of the droplet till its dislodgment are provided. • Data related to the changes of the pressure profile along the system are provided. The problem of ejection of a droplet from a pore opening into a reservoir appears in many fields including pharmaceutical, food, chemical, and several other industries. In this work, we are interested in investigating the onset of dislodgment of such an emerging droplet. A one-dimensional model is developed that describes the dynamics of this process under quasistatic assumptions. Fluid inertia, the dynamic nature of the contact angle, as well as the entrance and exit hydrodynamic effects are ignored. Fluid inertia may be important at the very early stage of the displacement process, after which its effect diminishes. It is hypothesized that the emerging droplet will dislodge the surface when the two contact lines associated with the two interfaces meet. The forces acting on this system include external pressures, viscous and capillary forces. The flow rate is influenced by the capillary pressure of the emerging nonwetting fluid when the advancing interface reaches the exit of the tube and starts to develop, then by the two interfaces when the wetting fluid starts to displace the wetting one. At the onset of dislodgment, the capillary pressure across the two interfaces equalizes. A computational fluid dynamics (CFD) study has been conducted to confirm the stated hypothesis and to provide a framework for the validation and verification of the developed model. The CFD model depicts the whole spectrum of processes involved from the start of injection of the nonwetting fluid towards the ejection of the droplet. The model, however, only considers the system when the wetting fluid starts to emerge from the exit of the tube into the reservoir. Comparisons between the model and the CFD analysis show a good match, which builds confidence in the modeling approach. Interesting results are obtained, particularly when the interfaces reach the exit of the tube.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.256
Teacher spread0.246 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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