MétaCan
Menu
Back to cohort
Record W4392520743 · doi:10.1061/9780784485347.013

Effect of Inherent Fabric on Cyclic Resistance of Granular Materials with Static Shear: A 3D-DEM Study

2024· article· en· W4392520743 on OpenAlexaff
Ali Salehi, Ming Yang, Mahdi Taiebat

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceShear (geology)Composite materialGeotechnical engineeringComputer scienceGeology

Abstract

fetched live from OpenAlex

The Kα parameter is a widely used factor that simplifies the interpretation of the influence of static shear stress on cyclic resistance of granular materials. However, it is still unclear whether the inherent fabric resulting from sample preparation protocols affects the Kα parameter. In this study, we use 3D-DEM to construct samples with polydisperse spherical particles with the same density and initial stress conditions, but different inherent fabrics characterized by coordination number and contact-normal fabric anisotropy. We conduct constant-volume cyclic simple shear tests on these samples and determine their cyclic resistance. Our simulation results indicate that inherent fabric does, quantitatively but not qualitatively, alter the Kα effect. Our results also show that inherent fabric influences the evolution of macro- and micro-parameters, such as mean stress drop, coordination number, fabric anisotropy, and coaxiality of principal directions of fabric and stress for different samples.

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 score0.711
Threshold uncertainty score0.383

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 head0.004
GPT teacher head0.216
Teacher spread0.212 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicGeotechnical Engineering and Soil StabilizationFrench-language works237,207