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Record W3108619400 · doi:10.1139/cgj-2019-0791

Normally loaded inclined strip anchors in cohesionless soil

2020· article· en· W3108619400 on OpenAlexvenueno aff
Nabil Al Hakeem

Bibliographic record

VenueCanadian Geotechnical Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsBreakoutEmbedmentGeotechnical engineeringFinite element methodGeologyAnchoringOffshore geotechnical engineeringDisplacement (psychology)Surface finishSubmarine pipelineStructural engineeringScale (ratio)Engineering

Abstract

fetched live from OpenAlex

Plate anchors are among the most effective anchorage systems that are widely used to resist horizontal and inclined uplift loads in many offshore and onshore applications. Previous research on plate anchors has largely focused on the horizontal or vertical breakout problems, with limited attention directed towards obtaining a full characterization of the effects of anchor orientation angle. The present study utilizes displacement-based finite element analyses to investigate the stability and performance of strip anchor embedded in cohesionless soil for plate inclination angles ranging from 0° to 90° from horizontal, where the applied load is normal to and acts at the center of the plate. This study investigates the effects of scale and roughness, along with the geometry of the failure mechanism for various plate orientations and embedment depths. The analyses, presented in terms of a non-dimensional breakout factor N q , show that the breakout factor increases significantly with an increase in the inclination, especially for angles greater than 45° in loose sand and greater than 60° in dense sand. The analyses also show that scale effects (anchor width) can affect capacity. Finite element analyses have been used to introduce simple design charts relating the breakout factor to the embedment depth and relative density. Comparisons to experimental and numerical studies showed good 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 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 categoriesMeta-epidemiology (narrow)
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 score0.284
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.010
GPT teacher head0.191
Teacher spread0.181 · 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.

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

Citations10
Published2020
Admission routes1
Has abstractyes

Explore more

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