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Record W2790612397 · doi:10.1063/1.5009466

Dynamic control of droplets and pockets formation in homogeneous porous media immiscible displacements

2018· article· en· W2790612397 on OpenAlexafffund
Tiago Lins, Jalel Azaiez

Bibliographic record

VenuePhysics of Fluids · 2018
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAmplitudeSurface tensionMechanicsViscosityPorous mediumPhysicsCapillary numberFlow (mathematics)Capillary actionHomogeneousPhase (matter)Displacement (psychology)Two-phase flowPorosityThermodynamicsMaterials scienceOpticsComposite material

Abstract

fetched live from OpenAlex

Interfacial instabilities of immiscible two-phase radial flow displacements in homogeneous porous media are analyzed for constant and time-dependent sinusoidal cyclic injection schemes. The analysis is carried out through numerical simulations based on the immersed interface and level set methods. The effects of the fluid properties and the injection flow parameters, namely, the period and the amplitude, on the formation of droplets and pockets are analyzed. It was found that larger capillary numbers or smaller viscosity ratios lead to more droplets/pockets that tend to appear earlier in time. Furthermore, the period and amplitude of the cyclic schemes were found to have a strong effect on droplets/pockets formations, and depending on their values, these can be enhanced or attenuated. In particular, the results revealed that there is a critical amplitude above which droplets and pockets formation is suppressed up to a specified time. This critical amplitude depends on the fluid properties, namely, the viscosity ratio and surface tension as well as on the period of the time-dependent scheme. The results of this study indicate that it is possible to use time-dependent cyclic schemes to control the formation and development of droplets/pockets in the flow and in particular to delay their appearance through an appropriate combination of the displacement scheme’s amplitude and period.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.830
Threshold uncertainty score0.374

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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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 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

Citations2
Published2018
Admission routes2
Has abstractyes

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