MétaCan
Menu
Back to cohort
Record W2750914564 · doi:10.1139/cgj-2016-0334

Combinations of soil materials for granular capillary barriers for minimizing rainfall infiltration and gas emission

2017· article· en· W2750914564 on OpenAlexvenueno aff
Limin Zhang, Yanzhe Ke

Bibliographic record

VenueCanadian Geotechnical Journal · 2017
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
FundersHong Kong University of Science and TechnologyNational Natural Science Foundation of China
KeywordsInfiltration (HVAC)SiltCapillary actionEnvironmental scienceMultiphysicsGeotechnical engineeringSoil waterWater retentionSoil scienceGeologyMaterials scienceComposite materialGeomorphology

Abstract

fetched live from OpenAlex

This paper presents a coupled air–water flow analysis to evaluate the performance of a three-layer capillary barrier for controlling water infiltration into and gas emission from a waste containment system in a high precipitation environment, and to optimize combinations of local soil layers for barrier construction. A multi-phase flow model is proposed considering the movements of the gas and water phases simultaneously. The governing partial differential equations are solved in COMSOL Multiphysics software. Several combinations of lean clay with sand (CL), clayey sand with gravel (SC), silty sand with gravel (SM), sandy silt (ML), and well-graded gravel with silt (GW–GM) are examined. The rates of percolation water and gas emission are used as indicators to compare the performance of different combinations. A fine-grained surface soil layer reduces both water infiltration and gas emission due to its low desaturation rate and high water-retention capacity. The coarse middle layer plays a critical role, promoting capillary effects and hindering water infiltration during rainfall as well as draining any infiltrated water or percolated gas.

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)0.001
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 score0.338
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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

Citations18
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicSoil and Unsaturated FlowFrench-language works237,207