MétaCan
Menu
Back to cohort
Record W2608961263 · doi:10.1017/jfm.2017.186

Resonance-like dynamics in radial cyclic injection flows of immiscible fluids in homogeneous porous media

2017· article· en· W2608961263 on OpenAlexafffund
Tiago Lins, Jalel Azaiez

Bibliographic record

VenueJournal of Fluid Mechanics · 2017
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaWestern Canada Research Grid
KeywordsMechanicsSurface tensionPorous mediumInstabilityMaterials scienceViscosityResonance (particle physics)Flow (mathematics)Viscous fingeringViscous liquidHomogeneousPorosityThermodynamicsPhysicsComposite material

Abstract

fetched live from OpenAlex

Interfacial instabilities of immiscible radial displacements in homogeneous porous media are analysed in the case of sinusoidal injection flows. The analysis is carried out through numerical simulations based on the immersed interface and level set methods. Investigations of the effects of the period of the sinusoidal injection flows revealed a novel resonance effect where, for a critical period, the number of fingers as well as their structures are considerably changed. The resonance in the flow development is clearly identified through the abrupt changes in the Fourier spectrum of the interface as well as quantitative characteristics of the flow in the form of the minimum and maximum radii of the interface. For the range of parameters examined in this study that correspond to instabilities dominated by viscous forces, the resonance period was found to correlate with a characteristic time of the flow and the fluids mobility ratio. This new physical phenomenon offers new perspectives for using the flow instability to determine important physical properties such as the viscosity and the surface tension of fluids.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 communication0.0000.000
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 head0.014
GPT teacher head0.242
Teacher spread0.227 · 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

Citations24
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Fluid MechanicsSame topicLattice Boltzmann Simulation StudiesFrench-language works237,207