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Record W2159892614 · doi:10.1139/t07-110

Laterally loaded rigid piles in cohesionless soil

2008· article· en· W2159892614 on OpenAlexvenueno aff
Wei Dong Guo

Bibliographic record

VenueCanadian Geotechnical Journal · 2008
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsPileGeotechnical engineeringNonlinear systemYield (engineering)ModulusSlip (aerodynamics)Displacement (psychology)Rotation (mathematics)Elastic modulusMechanicsYield surfaceStructural engineeringGeologyMaterials scienceMathematicsEngineeringGeometryPhysicsConstitutive equationFinite element methodComposite material

Abstract

fetched live from OpenAlex

In this paper, limiting force profile for laterally loaded rigid piles in sand is differentiated from the on-pile force profile, from which elastic–plastic solutions are established and presented in explicit expressions. Nonlinear responses of the piles are characterized by slip depths mobilized from mudline and the pile-tip. At the states of tip-yield and rotation point yield, expressions for some critical depths are developed, which allow the on-pile force profiles to be constructed. The solutions and the expressions are developed concerning a constant subgrade modulus (k) and a linearly increasing modulus with depth (Gibson k), respectively. Capitalized on three measurable parameters, the solutions agree well with measured data and numerical predictions. Nondimensional responses are presented for various eccentricities at the tip-yield state and in some cases at the rotation point yield state. Nonlinear responses are obtained for typical eccentricities from elastic state right up to failure. Comments are made regarding displacement-based capacity. A case study is elaborated to illustrate (i) the use of the current solutions; (ii) the impact of the k distributions; (iii) the evaluation of stresses on pile surface; and (iv) the deduction of soil modulus. The current solutions are easily implemented and suitable for general design.

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: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.964

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 head0.011
GPT teacher head0.177
Teacher spread0.166 · 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

Citations46
Published2008
Admission routes1
Has abstractyes

Explore more

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