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Record W2011929450 · doi:10.1139/t08-050

A numerical study into lateral cyclic nonlinear soil–pile response

2008· article· en· W2011929450 on OpenAlexaffvenue
Nii Allotey, M. Hesham El Naggar

Bibliographic record

VenueCanadian Geotechnical Journal · 2008
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversity of British ColumbiaWestern University
FundersUniversity of California, DavisUniversità degli Studi di Pavia
KeywordsPileGeotechnical engineeringFoundation (evidence)StiffnessGeologyNonlinear systemStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Pile foundations are generally designed to resist both axial and lateral loads. Under lateral cyclic loading, the response of the pile foundation is affected by factors such as soil and pile yielding, gapping, and soil cave-in. These factors directly influence the effective lateral stiffness and strength of the foundation and can govern the design. In this paper, two case studies of single piles, one in clay and one in sand, are used to examine the influence of the aforementioned factors on nonlinear cyclic response of piles. The numerical study is conducted using a recently developed beam on a nonlinear Winkler foundation (BNWF) model. The results of the study point to the important role soil cave-in and recompression play in the cyclic soil–pile response, and elucidate how this could particularly be beneficial to piles that develop plastic hinges below ground level.

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)0.002
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.210
Teacher spread0.201 · 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

Citations75
Published2008
Admission routes2
Has abstractyes

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