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Record W2292351177 · doi:10.1139/cgj-2015-0394

Winkler load-transfer analysis for laterally loaded piles

2016· article· en· W2292351177 on OpenAlexvenueno aff
Chenrong Zhang, Jian Yu, Maosong Huang

Bibliographic record

VenueCanadian Geotechnical Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsPileElastic modulusEmbedmentGeotechnical engineeringStiffnessSubgradeStructural engineeringLinear elasticityElasticity (physics)ModulusBoundary element methodFinite element methodGeologyMaterials scienceMathematicsEngineeringGeometryComposite material

Abstract

fetched live from OpenAlex

The Winkler modulus for a vertical beam buried in elastic soil is reassessed for the problem of a horizontal loaded pile in the framework of linear elasticity. By matching the integral solution in elastic continuum and the expression with the elastic Winkler modulus, the subgrade modulus of an infinitely long pile embedded into elastic space is obtained first. Then the influence of embedment depth and pile rigidity on the subgrade modulus is evaluated by virtue of Mindlin’s and Kelvin’s solutions, which gives the variation of the Winkler spring stiffness along the pile length. Comparison of the results by the present method for single piles in homogeneous and nonhomogeneous soils has shown good agreement with those obtained from the more rigorous elastic continuum solutions and boundary element method, which also revealed the disadvantage of the conventional Winkler expression in evaluating the displacement of the pile. Finally, the present method is used to analyze the pile–soil–pile interaction of a pile group, which also shows good agreement with the finite element method and the elastic continuum method, and proves the feasibility of extending the active subgrade modulus into the realm of the horizontal loaded pile group.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score0.741

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 integrity0.0000.000
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 head0.008
GPT teacher head0.192
Teacher spread0.184 · 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

Citations35
Published2016
Admission routes1
Has abstractyes

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