MétaCan
Menu
Back to cohort
Record W4386360130 · doi:10.1139/cgj-2023-0123

Analytical and numerical models for strain and load calculations for geosynthetic liner systems on steep slopes

2023· article· en· W4386360130 on OpenAlexafffundvenue
Yan Yu, R. Kerry Rowe

Bibliographic record

VenueCanadian Geotechnical Journal · 2023
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaSouthwest Jiaotong University
KeywordsTensile strainGeotechnical engineeringUltimate tensile strengthStiffnessGeotextileSettlement (finance)GeosyntheticsStrain (injury)Environmental scienceMaterials scienceStructural engineeringGeologyEngineeringComposite materialComputer science

Abstract

fetched live from OpenAlex

The paper develops an analytical model based on the force equilibrium for the design of steep slope geosynthetic liner systems to overcome downdrag loads from waste settlement. This analytical model calculates the required tensile stiffness for a high strength/stiffness geotextile (HS-GTX) reinforcement over the GMB to limit the maximum HS-GTX tensile strain to 5% and the maximum GMB strain to 4% on the side slope. The numerical model illustrates the need for reducing the GMB tensile strains for a single GMB liner on a steep landfill slope and confirms that the use of a HS-GTX over the GMB is able to limit the maximum HS-GTX and GMB tensile strains to the acceptable strain levels. The analytical model developed in this paper is a practical tool for preliminary design to limit tensile strains of the HS-GTX and GMB in a steep slope geosynthetic liner system.

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)0.001
metaresearch head score (Gemma)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.022
GPT teacher head0.229
Teacher spread0.207 · 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

Citations1
Published2023
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and Soil StabilizationFrench-language works237,207