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Record W2768062654 · doi:10.1002/cjce.23071

Numerical simulation of a semi‐industrial scale CFB riser using coarse‐grained DDPM‐EMMS modelling

2017· article· en· W2768062654 on OpenAlexvenueno aff
Muhammad Adnan, Nan Zhang, Fangfang Sun, Wei Wang

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsDragMechanicsParticle (ecology)Range (aeronautics)Work (physics)Scale (ratio)Eulerian pathPhysicsComputer simulationStatistical physicsMaterials scienceThermodynamicsGeology

Abstract

fetched live from OpenAlex

Abstract In this work, a coarse‐grained Dense Discrete Phase Model (DDPM) coupled with the Energy‐Minimization Multi‐Scale (EMMS) drag, was used to simulate the hydrodynamics of a 3D semi‐industrial scale Circulating Fluidized Bed (CFB) with Geldart A particles. The effect of particle numbers in a parcel, an important parameter in a coarse‐grained approach, was investigated. It was found that when parcel diameter falls into the size range of clusters, simulation results are insensitive to particle number in a parcel and generally agree with the experimental data. Further, a comparison between DDPM and Eulerian Two‐Fluid Modelling (TFM) approaches was investigated, both coupled with EMMS and conventional homogenous drag. The simulation results suggested that the effect of meso‐scale structures on drag force needs to be considered in both modelling approaches.

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 score0.090
Threshold uncertainty score0.625

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 integrity0.0000.001
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 head0.034
GPT teacher head0.220
Teacher spread0.186 · 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

Citations26
Published2017
Admission routes1
Has abstractyes

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