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Record W4402707362 · doi:10.1139/cgj-2023-0090

Large deformation analysis of intermittent pile penetration into dense sand incorporating a state-dependent Mohr–Coulomb model

2024· article· en· W4402707362 on OpenAlexvenueno aff
R. YE, Zhongyuan Huang, Zhongxuan Yang, Ning Guo, R. J. Jardine, Shao Jun Fu

Bibliographic record

VenueCanadian Geotechnical Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringMohr–Coulomb theoryGeologyPileDeformation (meteorology)Penetration (warfare)Finite element methodEngineeringStructural engineering

Abstract

fetched live from OpenAlex

The challenges of predicting the stresses acting around piles driven in sand limits meaningful analysis of their single and group loading responses, aging processes and scale/in-situ stress level dependency. Benchmark local stresses measurements made in the sand mass and pile shaft in Calibration Chamber (CC) models show that sharply different regimes act when the pile is either penetrating or temporarily stationary. This paper presents an Arbitrary Lagrangian–Eulerian (ALE) finite element simulation of installation into dense sand, highlighting the stress changes developed between intermittent penetration stages and exploring the effects of initial stress level. The installation by cyclic jacking of closed-ended model piles studied in a highly instrumented CC experiments is simulated with a state-dependent Mohr–Coulomb model calibrated to high-quality element tests on the sand employed. The predicted pile head loads and local stresses are compared with the CC experiments, showing generally good agreement over the lower parts of the pile shaft while also matching key field-scale trends from CPT-based practical design approaches. More advanced constitutive modeling appears necessary to eliminate discrepancies noted over the higher shaft levels, which may be linked to currently neglected aspects of the sands’ highly nonlinear behavior, including grain crushing and hysteresis under cyclic loading.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.209
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2024
Admission routes1
Has abstractyes

Explore more

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