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Record W2029249345 · doi:10.1103/physreve.76.066309

Lattice-Boltzmann simulation of solvent diffusion into oil-saturated porous media

2007· article· en· W2029249345 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhysical Review E · 2007
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLattice Boltzmann methodsPorous mediumSolventDiffusionMaterials scienceStatistical physicsPorosityLattice (music)ThermodynamicsMechanicsPhysicsChemistryOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

We simulated the diffusion process into oil-saturated porous media using the modified diffusion-limited aggregation and the lattice Boltzmann method algorithms. The results were matched to visual experiments for cocurrent (two sides of the model open to flow) and countercurrent (only one side of the model open to flow) diffusion for horizontally and vertically positioned samples. The model saturated with oil was exposed to pentane in order for a miscible interaction to take place. These experiments mimic the transfer between the rock matrix and fracture during gas or liquid solvent injection for enhanced oil recovery, underground waste disposal, groundwater contamination, and CO2 sequestration in naturally fractured reservoirs. Finger development at the early stages of the process was controlled by oil viscosity and the interaction type dictated by the boundary conditions. The convective transport driven by the buoyancy that was experimentally observed on vertically oriented samples and transfer driven by diffusion on the horizontal ones were captured in the LBM simulation of the process.

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.

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 score0.634
Threshold uncertainty score0.705

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.023
GPT teacher head0.314
Teacher spread0.290 · 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