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Record W1969070800 · doi:10.1139/cgj-2014-0538

Three-dimensional behavior of biaxial geogrid in a piled embankment: numerical investigation

2015· article· en· W1969070800 on OpenAlexvenueno aff
Kangyu Wang

Bibliographic record

VenueCanadian Geotechnical Journal · 2015
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsOrthotropic materialGeogridIsotropyParametric statisticsTrussGeotechnical engineeringStructural engineeringFinite element methodTension (geology)Materials scienceGeologyEngineeringComposite materialMathematicsReinforcementPhysicsUltimate tensile strength

Abstract

fetched live from OpenAlex

Biaxial geogrid in current research is oversimplified, and the three-dimensional orthotropic nature of the biaxial geogrid has not been fully understood in numerical investigations. A comparative study on three modeling approaches for the biaxial geogrid is presented in this paper, including the isotropic membrane model, the orthotropic membrane model, and the truss element model. It shows that the orthotropic membrane model yields practically identical results of the maximum geogrid tension when compared with the truss element model, whereas the isotropic membrane model tends to yield values that are approximately 33% larger. A parametric study shows that the pile spacing has the strongest influence on the maximum geogrid tension. The comparison of four analytical methods with the orthotropic membrane model shows that the British standard (BS) 8006 (published in 2010) and EBGEO (published in 2011) methods greatly overestimate the geogrid tension, while the method presented by Zhuang et al. (published in 2014) results in closer agreement.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.205
Teacher spread0.187 · 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

Citations60
Published2015
Admission routes1
Has abstractyes

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