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Record W2083929945 · doi:10.1029/2006gl027275

Trapping zones: The effect of fracture roughness on the directional anisotropy of fluid flow and colloid transport in a single fracture

2006· article· en· W2083929945 on OpenAlexaff
David F. Boutt, Giovanni Grasselli, J. T. Fredrich, Benjamin K. Cook, John R. Williams

Bibliographic record

VenueGeophysical Research Letters · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFracture (geology)Surface finishMaterials scienceAnisotropySurface roughnessColloidFlow (mathematics)Fluid dynamicsPhase (matter)MechanicsComposite materialGeologyOpticsChemistry

Abstract

fetched live from OpenAlex

In this paper we quantify the influence of geometry and distribution of surface roughness to the directional anisotropy of fluid flow and transport properties of a single fracture. Roughness of fractures appears to have first order control on how they behave mechanically and hydraulically. We directly quantified the surface roughness of a single fracture using high‐resolution laser scanning confocal microscopy. This roughness was input into directly coupled numerical models of fluid flow and transport. We simulated the transport of colloids (microspheres) through the fracture. We found tailing in the breakthrough and sensitivity of the breakthrough to flow direction in the fracture. Microspheres were observed to be trapped in low velocity zones on the lee side of fracture walls. This was not observed in smooth or sinusoidal varying fracture wall geometries. These observations have significant implications for quantifying the transport of dissolved and solid phase materials (colloids) through fractured rock.

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 score0.004
Threshold uncertainty score0.009

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 communication0.0010.000
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 head0.012
GPT teacher head0.248
Teacher spread0.237 · 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

Citations167
Published2006
Admission routes1
Has abstractyes

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