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Record W2936658855 · doi:10.1139/cgj-2018-0384

Improved understanding of geogrid response to pullout loading: insights from three-dimensional finite-element analysis

2019· article· en· W2936658855 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Geotechnical Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGeogridGeotechnical engineeringFinite element methodReinforcementGeosyntheticsStructural engineeringEngineeringMaterials scienceGeology

Abstract

fetched live from OpenAlex

Soil reinforcement has rapidly become one of the most common soil improvement techniques used in geotechnical engineering. Understanding the behavior of a geogrid under pullout loading is essential for the analysis and design of reinforced soil systems. The overall behavior of reinforced soils is generally dependent on the properties of the geogrid material, the backfill soil, and the interface condition. Modeling the three-dimensional aspects of soil–geogrid interaction under pullout loading condition is numerically challenging and requires special consideration of the different modes of resistance that contribute to the pullout capacity of the geogrid reinforcement. This study describes the results of a three-dimensional finite-element analysis that has been developed to investigate the behavior of a biaxial geogrid embedded in granular backfill material and subjected to pullout loading. The modeling approach considers the noncontinuous nature of the geogrid geometry and the elastoplastic response of the geogrid material. Model validation is performed by simulating laboratory-size pullout test and comparing the experimental data with the analytical as well as numerically calculated results. The detailed behavior of the geogrid and the surrounding backfill is investigated using the proposed numerical approach. Conclusions are made to highlight the suitability of this technique for analyzing similar soil–structure interaction problems.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.199
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