MétaCan
Menu
Back to cohort
Record W2019399864 · doi:10.1615/jpormedia.v10.i4.30

New Viscous Fingering Mechanisms at High Viscosity Ratio and Peclet Number Miscible Displacements

2007· article· en· W2019399864 on OpenAlexaff
Md. Nazrul Islam, Jalel Azaiez

Bibliographic record

VenueJournal of Porous Media · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPéclet numberViscous fingeringMechanicsHele-Shaw flowInstabilityFlow (mathematics)ViscosityFractalMaterials sciencePhysicsMathematicsOpen-channel flowPorous mediumMathematical analysisPorosityComposite material

Abstract

fetched live from OpenAlex

Full nonlinear simulation of the viscous fingering instability of miscible flow displacements in a rectilinear Hele-Shaw cell are conducted using a hybrid numerical algorithm. The algorithm allowed the modeling of the flow at relatively high values of the mobility ratio and Peclet number, representing the ratio of convective and dispersive forces. New finger structures, some reminiscent of fractal patterns observed in previous experimental studies, are reported. An explanation of the mechanisms responsible for the new finger structures is presented based on the development of the flow velocity field. The flow is also characterized qualitatively through a spectral analysis of the average concentration and an analysis of the variations of the relative finger width and relative contact area. General observations regarding the conditions for the development of complex finger structures are presented.

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 score0.001
Threshold uncertainty score0.003

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 studies0.0000.001
Scholarly communication0.0010.000
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 head0.005
GPT teacher head0.233
Teacher spread0.228 · 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

Citations13
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Porous MediaSame topicTheoretical and Computational PhysicsFrench-language works237,207