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Record W4353040048 · doi:10.1002/nag.3520

Experimental and modelling investigation of vibration‐induced fluidization in sheared granular soils

2023· article· en· W4353040048 on OpenAlexaff
Tao Xie, Peijun Guo, Dieter Stolle

Bibliographic record

VenueInternational Journal for Numerical and Analytical Methods in Geomechanics · 2023
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsMcMaster University
Fundersnot available
KeywordsFluidizationVibrationMesoscopic physicsShearing (physics)Granular materialMechanicsGeotechnical engineeringTriaxial shear testDilatantMaterials scienceShear (geology)GeologyPhysicsComposite materialFluidized bedThermodynamics

Abstract

fetched live from OpenAlex

Abstract Vibration‐induced fluidization (ViF) is a phenomenon where a granular medium completely loses shear resistance or flows continuously under vibration and thus behaves like a fluid without invoking remarkable excess pore pressure. This paper attempts to investigate ViF through a series of modified triaxial tests and using an extended shear‐transformation‐zone (STZ) model that correlates macroscopic plastic deformation to the motion of internal mesoscopic weak spots (i.e., STZs) within granular materials. The test results revealed that the ViF may take place when the vibration is applied at either critical or non‐critical states. Theoretical analyses using the extended STZ model show that the vibration intensity required to cause fluidization increases linearly with the initial quasi‐static shear stress level at which vibration is imposed. The model results are generally consistent with experimental data, indicating that the extended STZ model has a desirable performance in simulating the fluidization of granular soil subjected to quasi‐static shearing and vibration simultaneously.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.814
Threshold uncertainty score0.435

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 integrity0.0000.000
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 head0.050
GPT teacher head0.349
Teacher spread0.298 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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