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Record W4212948127 · doi:10.1002/cjce.24389

<scp>DEM</scp> simulations of spherical particle–particle collisions

2022· article· en· W4212948127 on OpenAlexvenueno aff
Wenming Liu, Wei Jiang, Honghong Zhang, Xuedong Liu, Hongmei Liu, Weiwen Zheng, Wei Zhao

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsnot available
FundersNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsDiscrete element methodBreakageCollisionParticle (ecology)RandomnessMechanicsMaterials scienceParticle sizeRelative velocityPhysicsComposite materialClassical mechanicsEngineeringComputer scienceGeology

Abstract

fetched live from OpenAlex

Abstract The randomness, diversity, and complexity of the high‐speed particle crushing process bring great difficulties to the theoretical analysis of powder engineering. In this paper, the discrete element method is used to simulate the collision of spherical particles, which provides a reference for studying the process and mechanism of crushing between particles under impact load. The Hertz–Mindlin with bonded contact model is used as the particle–particle contact model. The central collisions of particles with different diameter ratios under different high‐speed motions and the eccentric collisions with different eccentricities are discussed. The results show that the bond damage increases with the increase of relative velocity in both centre impact and eccentric impact. In centre collisions, particles of smaller objects are more fragmented than particles of larger objects. For smaller target particles, the larger the diameter ratio is, the more particle elements are detached from the target particles, and the greater the bond breakage rate. For larger target particles, the larger the diameter ratio is, the less the particle element falls off and the smaller the bond breakage rate. This provides guidance for the collision and crushing of particles with different particle size ratios and different eccentricities during high‐speed motion in engineering applications in the future.

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 score0.029
Threshold uncertainty score0.335

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 head0.012
GPT teacher head0.201
Teacher spread0.188 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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