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Record W2957276020 · doi:10.1002/cjce.23597

Pressure‐driven displacement flows of yield stress fluids: Viscosity ratio effects

2019· article· en· W2957276020 on OpenAlexafffundvenue
Ali Eslami, Roozbeh Mollaabbasi, A. Roustaei, Seyed Mohammad Taghavi

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2019
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaIran National Science FoundationCanada Foundation for Innovation
KeywordsMechanicsLaminar flowDisplacement (psychology)Reynolds numberFroude numberViscosityDimensionless quantityNewtonian fluidBingham plasticFlow (mathematics)Materials scienceThermodynamicsPhysicsRheologyTurbulence

Abstract

fetched live from OpenAlex

Abstract We numerically investigate pressure‐driven, density‐unstable displacement flows of two miscible fluids along a near‐horizontal 2D channel. The displacing fluid is a Newtonian fluid, slightly heavier than the displaced yield stress (Bingham) fluid. The imposed displacement flow is laminar. We show that the displacement flow is mainly governed by five dimensionless numbers, and their combinations, including the Reynolds number ( Re ), the Bingham number ( Bn ), the densimetric Froude number ( Fr ), the viscosity ratio ( m ), and the channel inclination angle ( β ). In this work, we primarily focus on the viscosity ratio and provide a detailed understanding of the flow behaviours via studying the effects of m on displacement flow patterns, regime classifications based on slump‐type and centre‐type displacement flow regimes, leading and trailing displacement front features, and finally the effects of m at different inclination angles.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.533

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 head0.004
GPT teacher head0.180
Teacher spread0.175 · 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 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

Citations14
Published2019
Admission routes3
Has abstractyes

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