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Record W1849308305 · doi:10.1029/2002wr001861

Pore network simulation of the dissolution of a single‐component wetting nonaqueous phase liquid

2003· article· en· W1849308305 on OpenAlexaff
Weishu Zhao, Marios A. Ioannidis

Bibliographic record

VenueWater Resources Research · 2003
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDissolutionMicromodelWettingMass transferMaterials sciencePhase (matter)Capillary actionPorous mediumDiffusionCapillary pressureChemical engineeringChemical physicsComposite materialPorosityChromatographyChemistryThermodynamics

Abstract

fetched live from OpenAlex

Soil wettability has been recently recognized as a factor that can dramatically influence the dissolution behavior of residual nonaqueous phase liquids (NAPL). A NAPL that wets the solid surface is trapped within the smaller pores and along the corners of pores invaded by water (the nonwetting phase). We present a two‐dimensional network simulator of wetting NAPL dissolution, inspired by observations of this process in transparent glass micromodels. The network model idealizes the pore space as a network of cubic pores connected by square tubes, following respective distributions. In accordance with micromodel observations, capillary equilibrium is assumed to exist between NAPL‐water interfaces along pore corners and within pores. Advection and diffusion of the organic dissolved in the aqueous phase, as well as dissolution mass transfer from residual NAPL, are explicitly accounted for in the model. Pores filled with NAPL are invaded at a rate which is controlled by mass transfer from dissolving thick NAPL films in pore corners and in order of increasing entry capillary pressure, resulting in quasi‐static drainage and fingering of the aqueous phase. Loss of NAPL continuity due to rupture of thick NAPL films and heterogeneity are found to affect profoundly the dissolution behavior, resulting in concentration tailing. The network simulator reproduces qualitatively the behavior observed in column experiments with oil‐wet media.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.038
GPT teacher head0.317
Teacher spread0.279 · 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

Citations27
Published2003
Admission routes1
Has abstractyes

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