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Modeling Effects of Moisture on Particle Breakage

2021· article· en· W3173829493 on OpenAlexaff
Younes Salami, Jean‐Marie Konrad

Bibliographic record

VenueInternational Journal of Geomechanics · 2021
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBreakageSaturation (graph theory)Particle (ecology)Materials scienceGeotechnical engineeringMoistureGranular materialParticle sizeMechanicsComposite materialGeologyMathematicsPhysics

Abstract

fetched live from OpenAlex

The recently developed framework for modeling grain breakage in granular materials is shown to be valid for saturated/unsaturated conditions. The model describes the initiation, development, and stabilization of breakage using three parameters, all depending on the strength of a representative particle size. When water is introduced, the strength of the soil's particles is expected to weaken, which leads to increased breakage intensities. The model is able to predict the early onset of crushing and the increase in particle breakage rate, both considered characteristic behaviors of a crushable granular medium in wet conditions. Initially dry and saturated model lines limit the evolution of the model parameters in the intermediate saturation states. A mid-loading change in the saturation of the granular medium results in an increased rate of particle breakage. The experimental data available in the literature is analyzed in light of the proposed model, which allows a better understanding of the development of particle breakage under the influence of water.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.389

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 head0.005
GPT teacher head0.204
Teacher spread0.199 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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