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Record W3088753311 · doi:10.1139/cgj-2020-0280

Towards a simple and reliable method for calculating uplift capacity of plate anchors in sand

2020· article· en· W3088753311 on OpenAlexvenueno aff
Anamitra Roy, Shiao Huey Chow, Conleth O’Loughlin, Mark Randolph

Bibliographic record

VenueCanadian Geotechnical Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
FundersLloyd's RegisterAustralian Government
KeywordsCentrifugeFinite element methodGeotechnical engineeringYield surfacePlasticityStructural engineeringAnisotropyShear (geology)Yield (engineering)MechanicsStress (linguistics)GeologyEngineeringMaterials scienceConstitutive equationPhysics

Abstract

fetched live from OpenAlex

This paper investigates the uplift capacity of horizontal plate anchors in sand through finite element analyses and centrifuge experiments. The finite element simulations adopt a sophisticated bounding surface plasticity model that accounts for stress- and density-dependent behaviour, as well as loading- and fabric-related anisotropic effects in sands. Failure mechanisms at peak anchor capacity show that failure occurs progressively, with a marked decrease in mobilised friction angle within the shear bands close to the anchor edge. Numerical simulations of a large set of centrifuge experiments on rectangular, strip, and circular plates at different relative densities and stress levels are in good agreement for dense conditions, but perform more poorly for loose conditions due mainly to the open cone yield surface in the bounding surface model. Equivalent comparisons with current limit equilibrium methods highlight the challenges in direct application of element-level strength equations. Finally, the paper proposes a modified limit equilibrium solution based on a “rigid-block” failure mechanism extending to the soil surface, but with anchor factors that encompass the results from the finite element simulations. The modified solution provides a higher level of agreement with results from a large database of plate and pipeline test data than existing limit equilibrium methods.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.731
Threshold uncertainty score0.628

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 studies0.0000.000
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 head0.017
GPT teacher head0.234
Teacher spread0.217 · 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 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

Citations35
Published2020
Admission routes1
Has abstractyes

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