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Record W2903242915 · doi:10.1139/cgj-2018-0660

Effect of interface transmissivity and hydraulic conductivity on contaminant migration through composite liners with wrinkles or failed seams

2018· article· en· W2903242915 on OpenAlexafffundvenue
R. Kerry Rowe, Ahmed AbdelRazek

Bibliographic record

VenueCanadian Geotechnical Journal · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaQueen's UniversityKillam TrustsOntario Innovation Trust
KeywordsHydraulic conductivityAquiferLeakage (economics)GeomembraneFinite element methodComposite numberGeotechnical engineeringConductivityHydraulic headMechanicsMaterials scienceGeologyGroundwaterStructural engineeringSoil scienceComposite materialEngineeringChemistryPhysicsSoil water

Abstract

fetched live from OpenAlex

The leakage and the peak chloride concentration in an aquifer for a single composite liner facility is modelled for (i) a hole in a geomembrane wrinkle and (ii) a failed seam. A method using a closed-form solution to calculate leakage together with a l½-dimensional (l½D) semi-analytic contaminant transport model is proposed, and the results compared with those obtained from two-dimensional (2D) finite element modelling (FEM). Leakage is shown to be highly dependent on the interaction between the interface transmissivity (θ) and hydraulic conductivity beneath the wrinkle (k b ). Similar leakages arising from different combinations of transmissivity and hydraulic conductivity are shown to have significantly different impacts on an underlying aquifer. Contaminant transport modelling is needed to assess this effect for the likely range of uncertainty regarding interface transmissivity (θ) and hydraulic conductivity. The 2D FEM is conceptually more comprehensive; however, using conventional software only a very limited size of problem could be accurately modeled given the greatly different scales that must be modelled. In contrast, the semi-analytic 1½D approach readily allowed consideration of the highly variable scales, and gave results at the down-gradient edge sufficiently similar to the 2D approach.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.988

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 studies0.0000.001
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 head0.010
GPT teacher head0.248
Teacher spread0.239 · 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

Citations47
Published2018
Admission routes3
Has abstractyes

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