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Record W2771355277 · doi:10.1139/cgj-2017-0137

Numerical and experimental study on influence of installation effects on behaviour of helical anchors in very dense sand

2017· article· en· W2771355277 on OpenAlexvenueno aff
Zorany Agudelo Perez, José Antonio Schiavon, Cristina de Hollanda Cavalcanti Tsuha, Daniel Dias, Luc Thorel

Bibliographic record

VenueCanadian Geotechnical Journal · 2017
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsCentrifugeDisplacement (psychology)Parametric statisticsGeotechnical engineeringStructural engineeringExperimental dataEngineeringComputer simulationWork (physics)GeologySimulationMechanical engineeringMathematics

Abstract

fetched live from OpenAlex

The use of helical anchors has been increasing in recent years; however, the current understanding of its behaviour does not allow for reliable estimates of uplift capacity and load–displacement response. The need for improvement of the design methods has motivated the present study, which investigates the effect of installation on the helical anchor response in very dense sand. This work is divided into three parts. The first part describes the results of centrifuge model tests and microtomographic analysis performed to examine the uplift response of a single-helix anchor and the soil disturbance caused by the installation process. The aim of these tests was to define appropriate hypotheses for the numerical prediction of helical anchor performance. In the second part, the load–displacement curve of a tested helical anchor was numerically simulated with the finite difference software FLAC 3D , considering the installation effect observed experimentally. In the third part of the paper, the adjusted numerical model was used in a parametric analysis to provide some guidelines for the design of helical anchors in dense sand. Additionally, from the results of the numerical investigation and experimental observations, two different approaches are presented for improving the accuracy of analytical predictions of helical anchor capacity. Both suggested methods showed good agreement with centrifuge and field testing data.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.642

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 head0.008
GPT teacher head0.232
Teacher spread0.223 · 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

Citations87
Published2017
Admission routes1
Has abstractyes

Explore more

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