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Steady granular flow in a rotating drum: A theoretical nonlocal model for characterizing stress, velocity, and packing fraction profiles, encompassing grain shape effects from convex to highly concave

2024· article· en· W4405736908 on OpenAlexaff
Jonathan Barés, Mathieu Renouf, Émilien Azéma

Bibliographic record

VenuePhysical Review Research · 2024
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsPolytechnique Montréal
FundersAgence Nationale de la Recherche
KeywordsAtomic packing factorDrumRegular polygonFlow (mathematics)MechanicsFraction (chemistry)Stress (linguistics)Materials sciencePhysicsMathematicsGeometryEngineeringChemistryMechanical engineeringChromatography

Abstract

fetched live from OpenAlex

In this work, we investigate the effect of particle shape, ranging from spherical to highly concave, on steady flows in a rotating drum, a system that facilitates a continuous transition from a jamming state at greater depths to an unjamming state at shallower regions. We develop an analytical model to elucidate granular behavior within the rotating drum: (i) First, by decomposing the shear stress, we reconcile the discrepancy between simulation data and theoretical predictions, establishing a relationship with the angle of repose. (ii) Second, we extend the generalized Bagnold scaling, coupled with a nonlocal fluidity relation based on packing fraction, providing a framework for a correlation between shear stress, shear rate, and packing fraction. Additionally, we introduce a characteristic length to quantify the influence of particle shape and drum speed. This analytical model offers explicit functional forms for physical quantity profiles, which are validated experimentally in a thin rotating drum and numerically in a two-dimensional rotating drum. Our results demonstrate that this model accurately describes the change in velocity from the bottom of the drum to the free surface. Moreover, for different shapes of particle and drum speeds, the characteristic length captures the interplay between shear stress, shear rate, and the variation of packing fraction. Published by the American Physical Society 2024

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.347
Teacher spread0.314 · 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.

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

Citations13
Published2024
Admission routes1
Has abstractyes

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