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Record W2022507914 · doi:10.1115/icnmm2012-73228

Experimental Investigation of the Flow Front Behind a Liquid-Air Interface for Capillary Flow

2012· article· en· W2022507914 on OpenAlexafffund
Prashant R. Waghmare, Debjyoti Sen, David S. Nobes, Sushanta K. Mitra

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates
KeywordsCapillary actionMeniscusMechanicsSurface tensionFlow (mathematics)Capillary numberMaterials scienceFlow visualizationPenetration (warfare)OpticsPhysicsEngineeringThermodynamicsComposite material

Abstract

fetched live from OpenAlex

An experimental system for understanding the flow field near the meniscus during the capillarity or under capillary action is developed. Capillary flow is one of the mechanisms for driving fluid in a microfluidic device. The literature highlights that a significant amount of work has been done on the theoretical understanding of the capillary transport in rectangular microchannels. However, these models for capillary flow neglect the flow behavior at the liquid-air interface, which may have a significant influence in terms of the velocity field and the transience of the penetration depth in the micro-capillary. The objective of the present study is to understand the flow development during the advancement of the meniscus. The aim is to elucidate the dynamics of the three phase contact line and other micro-scale effects during the capillarity. A μ-PIV technique has been used to study the flow development near the meniscus and the results are further refined using a hybrid μ-PIV/PTV technique. Effects of surface tension in the fully developed flow regime during the advancement of meniscus are studied in detail. Variations in the centreline velocity of the progression of the meniscus and temporal variations in the development of flow are identified as possible areas for departure from theory.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score1.000

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)0.0010.000

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 head0.032
GPT teacher head0.268
Teacher spread0.236 · 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.

Study designBench or experimental
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

Citations2
Published2012
Admission routes2
Has abstractyes

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