MétaCan
Menu
Back to cohort
Record W2100606792 · doi:10.1115/fedsm2012-72068

Interactions Between High-Viscosity Droplets Deposited on a Surface: Experiments and Simulations

2012· article· en· W2100606792 on OpenAlexafffund
J. Esmaeelpanah, Alireza Dalili, S. Chandra, J. Mostaghimi, Hong-Jun Fan, Hao‐Chung Kuo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsUniversity of Toronto
FundersGeneral Motors of Canada
KeywordsSurface tensionVolume of fluid methodCoalescence (physics)MechanicsViscosityMaterials scienceFree surfaceWeber numberInertial frame of referenceFlow (mathematics)PhysicsClassical mechanicsComposite materialThermodynamics

Abstract

fetched live from OpenAlex

A combined numerical and experimental investigation of coalescence of droplets of highly viscous liquids dropped on a surface has been carried out. Droplets of 87 wt% glycerin-in-water solutions with viscosity 110 centistokes were deposited sequentially in straight lines onto a flat, solid steel plate and droplet impact photographed. Impacting droplets spread on the surface until liquid surface tension and viscosity overcame inertial forces and the droplets recoiled, eventually reaching equilibrium. Droplet center-to-center distance was varied and droplet line length was measured from photographs. As droplet spacing was increased there was less interaction between the droplets. A three dimensional parallel code has been developed to simulate fluid flow and free surface interaction by solving the continuity, momentum and volume-of-fluid (VOF) equations. The two-step projection method was employed to solve the governing equations for the whole domain including both liquid and air phases. The continuum-surface-force (CSF) scheme was applied to model surface tension and the piecewise-linear-interface-construction (PLIC) technique used to reconstruct the free surface. Computer generated images of impacting droplets modeled droplet shape evolution correctly and compared well with photographs taken during experiments. Accurate predictions were obtained for droplet line length during spreading and at equilibrium.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.356

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 head0.020
GPT teacher head0.261
Teacher spread0.241 · 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 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

Citations0
Published2012
Admission routes2
Has abstractyes

Explore more

Same topicFluid Dynamics and Heat TransferFrench-language works237,207