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Record W2510165560 · doi:10.1061/9780784480144.043

Hydraulic Conductivity of Bentonite-Polymer Geosynthetic Clay Liners in Coal Combustion Product Leachates

2016· article· en· W2510165560 on OpenAlexaff
Hulya Salihoglu, Jiannan N. Chen, William J. Likos, Craig H. Benson

Bibliographic record

VenueGeo-Chicago 2016 · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsGolder Associates (Canada)
FundersU.S. Environmental Protection Agency
KeywordsLeachateHydraulic conductivityBentoniteGeosynthetic clay linerMaterials scienceConductivityCoalGeotechnical engineeringComposite materialChemistryWaste managementEnvironmental scienceGeologyEnvironmental chemistrySoil waterSoil scienceEngineering

Abstract

fetched live from OpenAlex

Hydraulic conductivity tests were conducted on two geosynthetic clay liners (GCLs) containing bentonite-polymer mixtures (BPMs) to investigate long-term hydraulic conductivity to coal combustion product (CCP) leachates. Permeant solution chemistries were synthesized to represent typical CCP leachate, predominantly divalent cation ash leachate, flue gas desulfurization residue leachate, high ionic strength leachate, and trona ash leachate. Hydraulic conductivity tests were conducted on non-prehydrated GCL specimens at an isotropic effective confining stress of 20 kPa in flexible-wall permeameters. Low hydraulic conductivities (<10-11 m/s) were maintained for both of the BPM GCLs in each of the permeant solutions. In contrast with what is commonly observed for conventional sodium bentonite GCLs, hydraulic conductivity of the BPM GCLs did not vary systematically with ionic strength of the permeant solution. Hydraulic conductivity of the GCLs was also not related systematically to swell index or fluid loss of the BPM, suggesting that index test procedures commonly adopted as surrogates for hydraulic conductivity for conventional GCLs may not be applicable to GCLs with BPMs.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

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 studies0.0000.000
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 head0.227
Teacher spread0.215 · 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 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

Citations21
Published2016
Admission routes1
Has abstractyes

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