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Record W2789234827 · doi:10.1149/08301.0127ecst

Numerical Study of Droplet Impact on Inclined Surface: Viscosity Effects

2018· article· en· W2789234827 on OpenAlexafffund
Mengcheng Jiang, Biao Zhou

Bibliographic record

VenueECS Transactions · 2018
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaCompute Canada
KeywordsViscosityMechanicsProton exchange membrane fuel cellMaterials scienceFlow (mathematics)Computer simulationContact angleTwo-phase flowBoundary value problemSimulationFuel cellsComposite materialEngineeringPhysicsChemical engineering

Abstract

fetched live from OpenAlex

Water management is still a critical challenge in the commercialization and development of proton exchange membrane fuel cell (PEMFC). Recently, in the numerical investigation of gas-liquid dynamics, the dynamic contact angle (DCA) has been considered as a crucial parameter and boundary condition in two-phase flow model. In this study, as one part of the robust DCA model development, the numerical simulation of glycerin droplet impact on inclined surface is conducted using DCA model. However, with the original parameters from the experiment, it is found that the numerical results have difficulty to match the experimental results. Considering the properties of the glycerin solution could vary in the experiment, the liquid viscosity is recalculated and the effects of different viscosities on droplet behaviors are investigated. The results show that higher liquid viscosity will make the droplet rebound from the surface more easily, and also shorten the sliding distance and droplet spreading length.

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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.018
GPT teacher head0.302
Teacher spread0.284 · 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

Citations6
Published2018
Admission routes2
Has abstractyes

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Same venueECS TransactionsSame topicSurface Modification and SuperhydrophobicityFrench-language works237,207