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Record W2080392222 · doi:10.1139/t00-122

An investigation of scaling and dimensional analysis of axially loaded piles

2001· article· en· W2080392222 on OpenAlexfundvenueno aff
Gabriel Sedran, Dieter Stolle, R. G. Horvath

Bibliographic record

VenueCanadian Geotechnical Journal · 2001
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMcMaster University
KeywordsPileScalingAxial symmetrySimilarity (geometry)Geotechnical engineeringFrustumSimilitudeScale (ratio)Structural engineeringFinite element methodOverburden pressureEngineeringMathematicsComputer scienceGeometryPhysics

Abstract

fetched live from OpenAlex

This paper investigates the use of the concepts of similarity and dimensional analysis to interpret results from reduced-scale models of axially loaded piles embedded in sand. These concepts are reviewed in the light of a pile–soil system and its response to static or half-sine impulsive loading. It is suggested that constitutive similarity between model and prototype responses can be fulfilled without scaling gravity, provided that a stress scaling factor equal to one is selected. The scaling factors are validated with numerical simulations via finite element analyses by comparing the results from full-scale and special reduced-scale pile–soil models. It is also shown that a frustum confining vessel has the potential to provide more realistic scaled responses than are obtained with the classical 1g devices. A series of pile test responses are simulated for different pile lengths and different coefficients of lateral earth pressure. A set of scaling factors is presented and a particular set of dimensionally homogeneous π groups is proposed to characterize the behaviour of the pile–soil system. Simulated responses are interpreted using the proposed π groups to obtain functional relations relevant to the pile–soil problem.Key words: reduced-scale modelling, dimensional analysis, similarity, model piles, sands.

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 score0.020
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.009
GPT teacher head0.195
Teacher spread0.186 · 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

Citations50
Published2001
Admission routes2
Has abstractyes

Explore more

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