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Record W2076744420 · doi:10.1504/ijesms.2015.068646

Variable-focus liquid lens simulation

2015· article· en· W2076744420 on OpenAlexaff
Osameh Ghazian, Jayshri Sabarinathan

Bibliographic record

VenueInternational Journal of Engineering Systems Modelling and Simulation · 2015
Typearticle
Languageen
FieldEngineering
TopicElectrowetting and Microfluidic Technologies
Canadian institutionsWestern University
Fundersnot available
KeywordsElectrohydrodynamicsMultiphysicsMechanicsFinite element methodSurface tensionViscosityCompressibilityNewtonian fluidConservation of massIncompressible flowFocus (optics)Non-Newtonian fluidClassical mechanicsPhysicsOpticsThermodynamicsElectric field

Abstract

fetched live from OpenAlex

A numerical study of liquid–based variable lenses is presented in this paper. The effect of applied voltage and the contact angle of the surface are taken into account. The conservation of mass and the Navier–Stokes equations for a Newtonian incompressible fluid were solved to model the fluid flow both inside and outside the droplet. The electrohydrodynamic equations have been solved using the commercial software COMSOL MULTIPHYSICS™ based on the finite element method. It was found that by increasing the viscosity ratio, the time response decreases which can be suitable for camera purposes.

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: none
Teacher disagreement score0.743
Threshold uncertainty score0.497

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 head0.024
GPT teacher head0.236
Teacher spread0.212 · 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
Published2015
Admission routes1
Has abstractyes

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