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Record W1961889268 · doi:10.1139/cgj-2015-0119

Modelling effects of pile diameter

2015· article· en· W1961889268 on OpenAlexaffvenue
W. D. Liam Finn, Jason Dowling

Bibliographic record

VenueCanadian Geotechnical Journal · 2015
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPileDeflection (physics)Structural engineeringGeotechnical engineeringStructural loadDynamic load testingFinite element methodDeflexionDisplacement (psychology)EngineeringPile capGeologyPhysics

Abstract

fetched live from OpenAlex

The most commonly used program for the analysis of piles under static lateral loading is LPILE. The program uses the nonlinear Winkler springs recommended by the American Petroleum Institute (API) to model soil–pile interaction. The p–y (load–displacement) curves were developed from field tests, with pile diameters in the range 0.324–0.67 m. When these p–y curves are used to analyze load tests on piles with larger diameters, the computed load–deflection curves underestimate the stiffnesses of the test piles. This effect is referred to as the pile diameter effect. In this technical note, a very different approach is presented to evaluate the pile diameter effect. Both LPILE and a continuum-based finite element program VERSAT-P3D were calibrated to closely simulate the results of two lateral load tests on small-diameter piles at two different sites. VERSAT-P3D modelled the volume of the pile and LPILE did not. Each program was used to develop p–y curves for increasingly larger pile diameters up to 2.0 m. An important finding for practice is that there was no pile diameter effect for displacements up to 60 mm. LPILE can be used with confidence in practice in this displacement range. Thereafter, the load–deflection curves from LPILE became softer and the pile diameter effect became evident.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.609

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 head0.013
GPT teacher head0.178
Teacher spread0.165 · 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

Citations29
Published2015
Admission routes2
Has abstractyes

Explore more

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