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Record W3168154317 · doi:10.1051/epjconf/202124911004

Geometrical network of granular materials under isochoric cyclic shearing

2021· article· en· W3168154317 on OpenAlexafffund
Ming Yang, Mahdi Taiebat, Patrick Mutabaruka, Farhang Radjaï

Bibliographic record

VenueEPJ Web of Conferences · 2021
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIsochoric processLiquefactionShearing (physics)AnisotropyMaterials scienceIsotropyDiscrete element methodMechanicsGranular materialDrop (telecommunication)Geotechnical engineeringComposite materialGeologyPhysicsEngineeringThermodynamicsMechanical engineering

Abstract

fetched live from OpenAlex

We use three-dimensional particle dynamics simulations to investigate the microstructure evolution of granular material subjected to isochoric cyclic shearing, driving the system to a liquefaction state. The cyclically sheared assembly presents a realistic macroscopic response as observed in physical experiments. By analyzing the contact network evolution in the post-liquefaction period, we show that the onset of liquefaction state is characterized by a sudden drop of coordination number and a fragile particle connectivity network. The simulation suggests a critical coordination number for exiting the liquefaction state. Evolution of fabric anisotropy combined with coordination number implies the isotropic and anisotropic gain or loss of contacts at certain durations of a post-liquefaction loading cycle.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.599
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.211
Teacher spread0.196 · 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

Citations2
Published2021
Admission routes2
Has abstractyes

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