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Record W2121296355 · doi:10.1139/cgj-2014-0506

Three-dimensional finite element modelling of a full-scale geosynthetic-reinforced, pile-supported embankment

2015· article· en· W2121296355 on OpenAlexaffvenue
R. Kerry Rowe, K.-W. Liu

Bibliographic record

VenueCanadian Geotechnical Journal · 2015
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsQueen's University
Fundersnot available
KeywordsGeotechnical engineeringPileGeogridSubsoilGeotextileLeveeSettlement (finance)Finite element methodGeosyntheticsReinforcementGeologySubgradeEngineeringFull scaleStructural engineeringSoil waterComputer science

Abstract

fetched live from OpenAlex

The performance of four sections of a full-scale embankment constructed on soft soil is examined using a fully coupled and fully three-dimensional finite element analysis. The four sections had similar embankment loadings but different improvement options (one unimproved, one with pile-support only, one with a single layer geotextile-reinforced platform and pile-support, and one with two layers of geogrid-reinforced platform and pile-support). Like the field data, the numerical results show that the inclusion of piles decreases the settlement at the subsoil surface to 52% of that for the unimproved section, and the addition of a single layer of geotextile reinforcement (J = 800 kN/m) further reduced settlement to only 31% of that of the unimproved section. The effects of geosynthetic reinforcement and multiple layers of reinforcement on the performance of the pile-supported embankment are discussed. The relative load transfer is calculated using eight existing methods and they are compared with the field measurements and numerical results.

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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.195
Teacher spread0.174 · 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

Citations153
Published2015
Admission routes2
Has abstractyes

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