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Record W7037174014

A discrete element study of wet particle-particle interaction during granulation in a spout fluidized bed

2009· other· en· W7037174014 on OpenAlexaboutno aff

Bibliographic record

VenueTU/e Research Portal (Eindhoven University of Technology) · 2009
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsRestitutionCoefficient of restitutionFluidizationEvaporationFlow (mathematics)GranulationFluidized bed combustionDiscrete element method
DOInot available

Abstract

fetched live from OpenAlex

In this article we study the effect of the inter-particle interaction on the bed dynamics, by considering a variable restitution coefficient. The restitution coefficient is varied in time and space depending on the moisture content due to the particle-droplet interaction and evaporation. This study is done computationally, by using an extended discrete element model (DEM). The examined flow regimes comprise the intermediate/spout- fluidization regime (B1), spouting-with-aeration regime (B2) and the jet-in-fluidized-bed regime (B3). For all flow regimes, the averaged bed height increases with decreasing restitution coefficient. Moreover, the averaged bed height for a variable restitution coefficient is larger for all flow regimes compared to a case with a constant restitution coefficient, indicating that the distribution of the restitution coefficient influences the bed dynamics. The effect of evaporation on the distribution of the restitution coefficient is only observed for the jet-in-fluidized-bed regime (B3), where the background velocity is relatively high leading to enhanced evaporation from the particles in the annulus region. This is reflected in the averaged bed height for the evaporation test case, which is larger compared to a test case without evaporation. A larger bed height for cases with variable restitution coefficient is due to the pressure build up in the spout region caused by the longer closing period of the spout channel. This is confirmed by the recorded pressure fluctuation signal and its root mean square which are larger for the cases with the variable restitution coefficient. On étudie dans cet article I'effet de I'interaction entre les particules sur la dynamique de lit, en considerant un coefficient de restitution variable. On a fait varier le coefficient de restitution dans le temps et dans I'espace en fonction de la teneur en humidite due à I'interaction particules-gouttelettes et a I'evaporation. Cette étude a été réalisée par ordinateur, à I'aide d'un modèle d'elements discrets étendu (DEM). Les regimes d'écoulernent examinés comprennent le régime de fluidisation intermediaire/jaillissement (BI), le régime de jaittissement avec aeration (B2) et le régime de jet en lit fluidisé (B3). Pour tous ces régimes d'écoulernent, la hauteur de lit moyennée augmente avec la diminution du coefficient de restitution. En outre, la hauteur de lit moyennée pour un coefficient de restitution variable est plus grande pour tous les régimes d'écoulernent comparativement au cas du coefficient de restitution constant, ce qui indique que la distribution du coefficient de restitution influence la dynamique de lit. L'effet de I'évaporation sur la distribution du coefficient de restitution s'observe seulement pour le régime de jet en lit fluidisé (B3), ou la vitesse de fond est relativement élevée, augmentant ainsi I'evaporation des particules dans la région de I'espace annulaire. Ceci se reflete dans la hauteur de lit moyennée pour le cas testé avec évaporation, qui est plus grande que dans le cas testé sans evaporation. Une hauteur de lit plus grande pour les cas avec coefficient de restitution variable est due à la montée de la pression dans la région du jaillissement qui est causée par la période de fermeture plus longue de la conduite de jaillissement. Ceci se continue par le signal de fluctuation de pression enregistré et son écart quadratique moyen qui sont plus grands pour les cas avec coefficient de restitution variable. © 2009 Canadian Society for Chemical Engineering.

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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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.327
Teacher spread0.295 · 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 designBench or experimental
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
Published2009
Admission routes1
Has abstractyes

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