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Record W2139662018 · doi:10.1139/t08-068

Experimental assessment of the response of sands under shear–volume coupled deformation

2008· article· en· W2139662018 on OpenAlexaffvenue
S. Sivathayalan, Paramaguru Logeswaran

Bibliographic record

VenueCanadian Geotechnical Journal · 2008
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsCarleton University
Fundersnot available
KeywordsStress pathGeotechnical engineeringPore water pressureTriaxial shear testShear stressOverburden pressureDilatantEffective stressGeologyDeformation (meteorology)Shear (geology)InflowMaterials scienceVolume (thermodynamics)Composite materialThermodynamics

Abstract

fetched live from OpenAlex

An experimental study of the behaviour of an alluvial sand under different strain increment paths representing shear–volume coupled deformation is presented. Both pore pressure and pore volume change simultaneously in these tests. Linear strain paths with different levels of limiting volumetric strain and nonlinear strain paths that simulate different pore pressure boundary conditions were applied to the soil specimen in the laboratory. The strain paths imposed included both expansive and contractive volumetric deformation. Nonuniform excess pore pressures generated during earthquakes (on account of the heterogeneity in natural soils) often lead to such deformation in situ following the end of strong shaking. The shear strength of the soil could decrease significantly when the pore pressure boundary conditions result in volume inflow that leads to a considerable reduction of the effective confining stress. The rate of volume inflow plays a significant role on the resulting stress–strain and pore pressure responses. Both the peak and the minimum shear strength mobilized during the test were significantly dependent on the strain path. The effective stress ratio at the instant of peak pore pressure is independent of the strain path followed, and it is equal to the effective stress ratio noted at the instant of phase transformation in undrained tests.

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 score0.038
Threshold uncertainty score0.416

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 head0.218
Teacher spread0.207 · 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

Citations30
Published2008
Admission routes2
Has abstractyes

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