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Record W2324200133 · doi:10.1115/fedsm-icnmm2010-31056

Viscous Oil-Water Flow in a Microchannel: Flow Patterns and Flow Development

2010· article· en· W2324200133 on OpenAlexaff
Hooman Foroughi, Masahiro Kawaji

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMicrochannelSilicone oilVolumetric flow rateMaterials scienceFlow (mathematics)ViscosityWater flowPetroleum engineeringMechanicsComposite materialGeologyGeotechnical engineeringNanotechnologyPhysics

Abstract

fetched live from OpenAlex

The flow characteristics of a highly viscous oil and water mixture in a circular microchannel have been investigated. Water and silicone oil with a viscosity of 863 mPa.s were injected into a fused silica microchannel with a diameter of 250 μm. Before each experiment, the microchannel was initially saturated with either oil or water. In the initially oil-saturated case, different liquid-liquid flow patterns were observed and classified over a wide range of oil and water flow rates. As a special case, the flow of water at zero oil flow rate in a microchannel initially filled with silicone oil was also studied. When the microchannel was initially saturated with water, the oil formed a jet in water at the injection point but developed an instability at the oil-water interface downstream and eventually broke up into droplets.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

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