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Record W2328925651 · doi:10.1139/cgj-2013-0457

Simultaneous gas and water flow in a damage-susceptible bedded argillaceous rock

2014· article· en· W2328925651 on OpenAlexaffvenue
T.S. Nguyen, A.D. Le

Bibliographic record

VenueCanadian Geotechnical Journal · 2014
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsCanadian Nuclear Safety Commission
FundersElectricité de FranceUniversité de Liège
KeywordsPermeability (electromagnetism)AnisotropyGeotechnical engineeringGeologySedimentary rockRelative permeabilityBedBeddingSaturation (graph theory)Pore water pressureFlow (mathematics)Water flowPetroleum engineeringMechanicsPorosityChemistry

Abstract

fetched live from OpenAlex

A mathematical model that couples the governing and constitutive equations of two-phase flow and mechanical equilibrium has been developed to simulate gas injection tests for both laboratory- and field-scale experiments. The model takes into consideration the inherent anisotropy of sedimentary rocks due to bedding by including an anisotropic elastoplastic model for the mechanical process and using an anisotropic permeability tensor for the flow processes for both water and gas. The gas and water flow rates are assumed to follow Darcy’s law. The relative permeability of each phase and their respective degrees of saturation are represented by the Van Genuchten’s functions. We simulated laboratory and field gas injection experiments in Opalinus clay, a candidate geological formation for the geological disposal of radioactive wastes. The numerical results show good agreement with the experimental data measured in these tests in terms of two-phase flow regimes and hydromechanical response at various monitoring locations. Damage zones, either pre-existing due to excavation or induced by high gas injection pressure, are shown to clearly influence the gas flow rates and directions and would need special consideration in the design and safety assessment of the repository system.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.900

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 integrity0.0000.001
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 head0.004
GPT teacher head0.177
Teacher spread0.172 · 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

Citations36
Published2014
Admission routes2
Has abstractyes

Explore more

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