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Record W1493761704 · doi:10.1029/2006wr004953

Influence of simple fracture intersections with differing aperture on density‐driven immiscible flow: Wetting versus nonwetting flows

2006· article· en· W1493761704 on OpenAlexaff
Sung‐Hoon Ji, Michael J. Nicholl, Robert J. Glass, Kang‐Kun Lee

Bibliographic record

VenueWater Resources Research · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsWettingCapillary actionMechanicsIntersection (aeronautics)Aperture (computer memory)Geotechnical engineeringFlow (mathematics)Materials scienceGeologyComposite materialPhysicsEngineeringStructural engineering

Abstract

fetched live from OpenAlex

We conducted laboratory experiments to evaluate the effects of simple fracture intersections with differing aperture on density‐driven immiscible wetting (water into air) and nonwetting (Trichloroethylene into water) flows, and analyzed them quantitatively. The experimental systems consisting of vertical and horizontal fractures were fabricated with glass for easy visualization. The aperture variation between intersecting fractures and the viscous force of the injected fluid were considered to be critical system parameters. Experimental results show the critical difference between the wetting and nonwetting flows by the intersection and viscous force, and subsequent mathematical analyses explain well our observations: The intersection acts as a capillary barrier (CB) for the wetting and capillary bridge for the nonwetting flows, and the viscous force of flowing fluids reduces the strength of CBs. The results of both laboratory experiments and mathematical analyses suggest that the fracture intersection with differing aperture can be a more significant factor controlling the network‐scale phase structure for the nonwetting than the wetting flows.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.514

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 studies0.0010.000
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 head0.016
GPT teacher head0.264
Teacher spread0.248 · 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 designObservational
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

Citations28
Published2006
Admission routes1
Has abstractyes

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