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Record W4296787997 · doi:10.1680/jgeot.22.00099

Development of extended STZ model for granular soils subjected to combined static loading and vibration

2022· article· en· W4296787997 on OpenAlexaff
Tao Xie, Peijun Guo, Dieter Stolle

Bibliographic record

VenueGéotechnique · 2022
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsMcMaster University
Fundersnot available
KeywordsShear matrixShear (geology)VibrationMaterials scienceGranular materialShear bandShear stressPlasticityMechanicsComposite materialPhysicsAcoustics

Abstract

fetched live from OpenAlex

The ‘shear-transformation zone’ (STZ), which may be referred to as a weak domain in granular material, is the main source of plastic deformations in non-cohesive soils such as sand or gravel. To theoretically investigate the vibration-induced shear resistance reduction (ViSRR) of granular materials, in this paper an extended STZ model is proposed that considers the coupling effect between vibration and quasi-static loadings. The framework of the model consists of three components: (a) the motion of STZs including the transition, creation and destruction of STZs; (b) the relation between the motion of small-scale STZs and the observable, macroscopic plastic strain; and (c) the evolution law of a ‘configurational temperature’ that reflects the energy that drives the motion of STZs. The conventional STZ model developed for amorphous materials is enhanced to accommodate both volumetric and shear deformations in the spatial stress state. Specifically, in addition to considering plastic shear strains induced by the change in STZ orientation as the result of the transition, as in conventional STZ models, the extended STZ model correlates plastic volumetric strains with the change in STZ amount resulted from creation and destruction.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.452
Threshold uncertainty score0.551

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 head0.014
GPT teacher head0.225
Teacher spread0.211 · 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 designBench or experimental
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

Citations11
Published2022
Admission routes1
Has abstractyes

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