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Record W2056206400 · doi:10.1615/ichmt.2008.cht.2290

NUMERICAL SIMULATION OF THE LIQUID EXTRACTION FROM A STRATIFIED LIQUID-VAPOR ZONE USING ELECTROHYDRODYNAMIC EFFECTS

2008· article· en· W2056206400 on OpenAlexaff
Hossam Sadek, James S. Cotton, C.Y. Ching

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsElectrohydrodynamicsElectric fieldMechanicsTwo-phase flowMomentum (technical analysis)Stratified flowMaterials scienceITIESVoltageFlow (mathematics)PhysicsElectrode

Abstract

fetched live from OpenAlex

A quasi-steady numerical methodology was developed to predict the liquid extraction from a stratified liquid-vapor zone due to electrohydrodynamics (EHD). The stratified liquid-vapor was in a tube, and a step DC voltage was applied using a central electrode along the tube axis. The solution for the electric field was coupled with the Navier-Stokes equations to determine the interfacial velocities. Here, the electric field imposes an interfacial force on the liquid interface, which was estimated using the equation developed by Stratton [1941] assuming a free charge interface. The electric field and the momentum equations were solved iteratively for small time steps, using the interfacial force due to the electric fields as the boundary condition at the liquid interface for solving for the velocity in the liquid phase. The position of the liquid interface for each iteration was updated using the interfacial velocity from the previous iteration. The numerical simulations were performed using a commercial finite element code. The liquid extraction times were estimated, and were found to be in good agreement with those estimated from flow visualization experiments.

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 score0.389
Threshold uncertainty score0.821

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 head0.008
GPT teacher head0.226
Teacher spread0.218 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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