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Potential for Desiccation of Geosynthetic Clay Liners Used in Barrier Systems

2013· article· en· W1981278836 on OpenAlexafffund
A. Hoor, R. Kerry Rowe

Bibliographic record

VenueJournal of Geotechnical and Geoenvironmental Engineering · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaResearch and Innovation FoundationMinistry of Environment
KeywordsDesiccationGeosynthetic clay linerGeotechnical engineeringSubsoilEnvironmental scienceGeosyntheticsWater contentSoil waterWater potentialAquiferGeologySoil scienceGroundwaterHydraulic conductivityEcology

Abstract

fetched live from OpenAlex

The potential for the desiccation of a geosynthetic clay liner (GCL) forming part of a single composite landfill liner is evaluated. A thermohydromechanical model is used to identify conditions likely to cause desiccation. Simulations for typical landfill conditions show that the potential risk of desiccation exists even at relatively low temperatures (i.e., 35°C). It is found that the water content of the GCL prior to waste placement, the liner temperature, the overburden stress, the grain size and water content of the subsoil, and the depth to aquifer all affect the potential for desiccation. The results suggest that the placement of GCLs directly over coarse-grained soils or drainage layers should be evaluated carefully. This study highlights the need for more research into the potential for GCL desiccation and, in particular, the need to establish water retention curves for different GCLs over a range of stresses and degrees of hydration before heating, so that the effect of stress and hysteresis on the potential for desiccation can be examined. The findings of this study are limited by the approximations and assumptions described in the paper and, even then, apply only to the GCL and conditions examined. Changing the assumptions may change the findings. The findings should not be generalized to other composite liners without independent verification. The results serve to identify some of the situations that may lead to GCL desiccation, and it is hoped that they will prompt more research on this important topic.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.523

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 integrity0.0000.000
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 head0.004
GPT teacher head0.185
Teacher spread0.180 · 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

Citations42
Published2013
Admission routes2
Has abstractyes

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