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Record W3198457146 · doi:10.1115/icnmm2020-1074

Slip in the Presence of Semi-Circular Menisci Between Parallel Ridges

2020· article· en· W3198457146 on OpenAlexaff
Lisa Steigerwalt Lam, Yuri S. Muzychka

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Thin Films
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsLaminar flowCurvatureSlip (aerodynamics)DragMaterials scienceMechanicsWettingMeniscusOpticsGeometryComposite materialPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract Surfaces which are structured on the micro- and nanoscale to resist wetting are being considered for internal flows due to their drag reducing properties in applications such as electronics cooling and lab-on-chip. Here, an expression is developed to characterize the hydrodynamic slip in a laminar flow which occurs near the surface for the case when positive meniscus curvature is present. The surfaces considered are composed of ridges oriented parallel to the flow. Curvature of the meniscus, which resides between the liquid in the Cassie state and the gas trapped in cavities between the ridges, results from the pressure difference between the liquid and the gas. The meniscus is considered shear free. The no slip condition exists at the tips of the ridges. Conformal maps from the literature are used to derive an expression which is a function of cavity fraction of the surface. The positive protrusion angle is 90 degrees. Cavity fractions range from 0 to 75%.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.018
GPT teacher head0.208
Teacher spread0.190 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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