MétaCan
Menu
Back to cohort
Record W3042022291 · doi:10.1139/cgj-2019-0243

Effect of density on skin friction response of piles embedded in sand by simple shear interface tests

2020· article· en· W3042022291 on OpenAlexvenueno aff
Kazem Fakharian, Nasrin Vafaei

Bibliographic record

VenueCanadian Geotechnical Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsPileGeotechnical engineeringStiffnessShear (geology)Materials scienceRelative densityNormal forceGeologyShear stressMechanicsDirect shear testSimple shearParasitic dragStructural engineeringComposite materialEngineeringPhysics

Abstract

fetched live from OpenAlex

This study focuses on a particular phenomenon related to the reduction in sand–pile skin friction with initial relative density increment from medium to dense. Frictional behaviour of a sand–pile interface is simulated using a simple shear-type device capable of inducing a constant normal stiffness condition. Sand–pile interface sliding and soil deformation components are distinguished quantitatively. The effects of initial relative density of sand, initial normal load, and constant normal stiffness on the magnitude of the pile skin friction and shear displacement at failure are examined. Results indicate that the magnitude of the mobilized shear stress at failure relies significantly on the shear stress state with respect to the inflexion point on the volume change graph, which is equivalent to the position of the peak stress ratio. Good correlations exist between results of this study and field data of several heavily instrumented piles embedded in dense to very dense sands. The presented procedure is a useful framework for establishing more accurate skin friction calculation methodologies and “t-z” curve developments of axially loaded piles.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.303
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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

Citations38
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and Soil MechanicsFrench-language works237,207