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Record W2887833473 · doi:10.1139/cgj-2018-0025

Analysis of cylindrical cavity expansion in anisotropic critical state soils under drained conditions

2018· article· en· W2887833473 on OpenAlexvenueno aff
K. Liu, S.L. Chen

Bibliographic record

VenueCanadian Geotechnical Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersLouisiana Transportation Research Center
KeywordsAnisotropyConsolidation (business)Geotechnical engineeringMechanicsParametric statisticsOrdinary differential equationEffective stressCritical state soil mechanicsSoil waterStress (linguistics)Hardening (computing)GeologyMaterials scienceDifferential equationMathematicsMathematical analysisEngineeringConstitutive equationPhysicsStructural engineeringComposite materialSoil scienceOptics

Abstract

fetched live from OpenAlex

This paper presents a semi-analytical solution for the drained cylindrical cavity expansion problem using the well-known anisotropic modified Cam clay model proposed by Dafalias in 1987. The prominent feature of this elastoplastic model, i.e., its capability to describe both the initial fabric anisotropy and stress-induced anisotropy of soils, makes the anisotropic elastoplastic solution derived herein for the cavity problem a more realistic one. Following the development by Chen and Abousleiman in 2013 of a novel solution scheme that establishes a link between the Eulerian and Lagrangian formulations of the condition of radial equilibrium, the plastic zone solution can eventually be obtained by solving a system of eight partial differential equations with the three stress components, three anisotropic hardening parameters, specific volume, and preconsolidation pressure being the basic unknowns. Parametric studies have been conducted to explore the influences of K 0 consolidation anisotropy and overconsolidation ratio (OCR), and their pronounced impacts on the stress patterns outside the cavity as well as on the development of stress-induced anisotropy are clearly observed.

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 score0.153
Threshold uncertainty score0.848

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 integrity0.0000.001
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 head0.242
Teacher spread0.231 · 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

Citations45
Published2018
Admission routes1
Has abstractyes

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