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Record W4288255305

Micro-mécanique des milieux granulaires triphasiques

2019· preprint· fr· W4288255305 on OpenAlexaff
J. Duriez, Richard Wan

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2019
Typepreprint
Languagefr
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMaterials science
DOInot available

Abstract

fetched live from OpenAlex

/ Le comportement mécanique des milieux granulaires triphasiques, tels que les sols partiellement saturés en eau, est étudié en combinant deux approches micro-mécaniques : une homogénéisation analytique avec des simulations numériques aux Éléments Discrets. Par homogénéisation, on exprime les contraintes macroscopiques de ces matériaux à partir des forces de contact inter-grains, des deux pressions différentes des fluides, et des efforts de tension superficielle, tous présents à l'échelle microscopique. L'expression µUNSAT ainsi obtenue associe de manière générale un caractère tensoriel (non-sphérique) aux différentes contributions, en accord avec la microstructure du matériau. Un modèle numérique aux Éléments Discrets permet ensuite de mesurer ces différentes contributions dans le cas d'un milieu granulaire idéal en conditions humides. Les résultats numériques démontrent l'anisotropie des contraintes capillaires dues aux phases fluides, et, dans une certaine mesure, le caractère effectif des contraintes dues aux forces de contact.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.210
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 source (direct Gemma or distilled Codex), 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

Citations0
Published2019
Admission routes1
Has abstractyes

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