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Record W7108079255 · doi:10.1051/epjconf/202534007006

Interplay of particle size distribution and relative density in cyclic liquefaction resistance

2025· article· en· W7108079255 on OpenAlexafffund

Bibliographic record

VenueEPJ Web of Conferences · 2025
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsUniversity of TorontoUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRelative densityShearing (physics)LiquefactionParticle sizeParticle-size distributionParticle (ecology)Coordination numberNumber density

Abstract

fetched live from OpenAlex

This study investigates the interplay of particle size distribution and relative density on the cyclic liquefaction resistance of sands using three-dimensional discrete element method simulations. Assemblies with varying coefficients of uniformity ( C u ) were prepared at two relative densities and underwent constant volume cyclic shearing at the same cyclic stress ratios until initial liquefaction. Results show a non-monotonic relationship between C u and liquefaction resistance: an initial increase in resistance with increasing C u , followed by a decrease beyond a critical C u value, consistently observed at both relative densities. Micromechanical analyses demonstrate that this trend correlates with the rate of decline of the mechanical coordination number during the pre-liquefaction phase. A power-law relationship is established between the cyclic resistance and the rate of coordination number reduction, providing insight into the underlying fabric evolution mechanisms.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.006
GPT teacher head0.223
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes2
Has abstractyes

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