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Record W2033786123 · doi:10.1139/t09-111

Drained instability of sand in plane strain

2010· article· en· W2033786123 on OpenAlexvenueno aff
Dariusz Wanatowski, Jian Chu, W. L. Loke

Bibliographic record

VenueCanadian Geotechnical Journal · 2010
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsInstabilityGeotechnical engineeringPlane stressLiquefactionGeologyRotational symmetrySoil liquefactionPlane (geometry)Triaxial shear testMechanicsShear (geology)EngineeringStructural engineeringMathematicsGeometryFinite element methodPhysicsPetrology

Abstract

fetched live from OpenAlex

Flowslide or failure of loose granular soil slopes is often explained using liquefaction or instability data obtained from undrained triaxial tests. However, under static loading conditions, the assumption of an undrained condition is not realistic for sand, particularly clean sand. Case studies have indicated that instability of granular soil can occur under essentially drained conditions (e.g., the Wachusett Dam failure in 1907). Laboratory studies on Changi sand by Chu et al. in 2003 have shown that sand can become unstable under completely drained conditions. However, these studies were carried out under axisymmetric conditions and thus, cannot be applied directly to the analysis of slope failures. In this paper, experimental data obtained from plane-strain tests are presented to study the instability behaviour of loose and dense sand under plane-strain conditions. Based on these test data, the conditions for the occurrence of drained instability in plane strain are established. Using the modified state parameter, the conditions for instability under both axisymmetric and plane-strain conditions can be unified. A framework for interpreting the instability conditions of sandy slopes developed under axisymmetric conditions also extends into plane-strain conditions.

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)0.001
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 score0.183
Threshold uncertainty score0.771

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.002
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 head0.006
GPT teacher head0.184
Teacher spread0.178 · 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

Citations42
Published2010
Admission routes1
Has abstractyes

Explore more

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