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Record W2943291977 · doi:10.1063/1.5090772

Interfacial instabilities of immiscible non-Newtonian radial displacements in porous media

2019· article· en· W2943291977 on OpenAlexafffund
Young H. Lee, Jalel Azaiez, Ian D. Gates

Bibliographic record

VenuePhysics of Fluids · 2019
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaWestern Canada Research Grid
KeywordsDeborah numberShear thinningPhysicsPower lawNon-Newtonian fluidNewtonian fluidDilatantShear rateMechanicsThermodynamicsShear (geology)InstabilityCapillary actionRheologyMaterials scienceComposite materialStatisticsMathematics

Abstract

fetched live from OpenAlex

Immiscible flows that involve radial displacements of shear-thinning or shear-thickening fluids by a Newtonian fluid in a homogeneous porous medium are modeled numerically. The interfacial instabilities are tracked in time for different values of the rheological parameters, namely, the Deborah number (De) and the power-law index (n), and are characterized through the effective number of fingers and the finger area density. The results of the study reveal that the effects of these two parameters on the instability are not monotonic, and it is found that the flow is least unstable for some critical value of either De or n. The dependence of these critical values, in particular, on the mobility ratio (M) and capillary number (Ca) is analyzed. It is found that when all other parameters are fixed, the critical Deborah number (Dec) increases as the power-law index increases in shear-thinning fluids or decreases in shear-thickening ones. Similarly, the critical power-law index (nc) increases with increasing (decreasing) Deborah number in shear-thinning (shear-thickening) flows. Furthermore, both critical parameters are found to vary monotonically with the mobility ratio, with the dependence most noticeable at small values of M. Their variation with the capillary number is however nonmonotonic reaching an extremum at an intermediate value of Ca. An examination of the rate of shear strain at the interface reveals that it consistently shows the smoothest variation and the smallest average value at the critical parameter.

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 score0.591
Threshold uncertainty score0.546

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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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

Citations24
Published2019
Admission routes2
Has abstractyes

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