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Record W2312640114 · doi:10.1139/t2012-045

Linkage between static and cyclic liquefaction of loose sand with a range of fines contents

2012· article· en· W2312640114 on OpenAlexvenueno aff
M. A. L. Baki, Md Mizanur Rahman, S. R. Lo, C. T. Gnanendran

Bibliographic record

VenueCanadian Geotechnical Journal · 2012
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersUniversity of New South Wales
KeywordsInstabilityLiquefactionVoid ratioGeotechnical engineeringShearing (physics)SofteningVoid (composites)Monotonic functionMaterials scienceSoil liquefactionGeologyComposite materialMechanicsMathematicsPhysics

Abstract

fetched live from OpenAlex

The underlying mechanism of static and cyclic liquefaction of loose contractant sandy soil is unstable behaviour associated with deviatoric strain-softening. Such unstable (strain-softening) behaviour has been referred to as static or cyclic instability depending on whether the loading condition is monotonic or cyclic. Past research into linkage between static instability and cyclic instability of sand with fines is based largely on comparing monotonic and one-way cyclic loading behaviour of specimens of the same void ratio and fines content. In this article, the authors attempt to link the condition that defines triggering of cyclic instability to that of static instability of specimens of different void ratios and fines contents. This is achieved by the proposed concept of equivalent granular state parameter. Two specimens are considered as equivalent if they have the same equivalent granular state parameters at the start of undrained shearing. The effective stress ratio at triggering of static instability can be used to predict impending cyclic instability of an equivalent specimen of different fines content and void ratio. This linkage between static and cyclic instability was evaluated for a wide range of fines contents, initial mean effective stresses, and types of cyclic loading. The last factor includes symmetrical and nonsymmetrical two-way cyclic loading.

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: Empirical
Teacher disagreement score0.616
Threshold uncertainty score0.478

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 head0.012
GPT teacher head0.198
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

Citations77
Published2012
Admission routes1
Has abstractyes

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