From fluidization regimes to mixing criteria: Insights into high‐density binary particle systems

Abstract A validated coarse‐grained computational fluid dynamics ‐ discrete element method (CFD‐DEM) framework is developed to investigate the flow and mixing behavior of ultra‐high‐density particles (6700–10,960 kg/m 3 ), far exceeding the density of conventional fluidization studies. Results show that the increases in a two‐segment fashion with density, deviating from classical predictions in the ultra‐dense regime. Despite low Archimedes numbers (9–15) predicting Group A classification, pressure fluctuation and bed expansion characteristics reveal a transition from Group B toward D behavior, demonstrating classification breakdown at extreme densities. For binary mixtures, pressure‐drop standard deviation serves as a dual diagnostic for both flow regimes and mixing states. Macroscopic mixing requires , with thresholds scaling nearly linearly with . Notably, systems with small density contrast achieve mixing more readily, even at higher absolute density. These findings provide a predictive framework for high‐density reactor design in nuclear‐fuel conversion.

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Publication Details

Journal
AIChE Journal
Published
2026-02-22
DOI
https://doi.org/10.1002/aic.70295
Primary Topic
Granular flow and fluidized beds
Type
article
Field-Weighted Citation Impact
0.00
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article

From fluidization regimes to mixing criteria: Insights into high‐density binary particle systems

Y. X. Zhang, Lei Zhang, Shuyue Li, Zhihong Mao
AIChE Journal
Granular flow and fluidized beds
article

From fluidization regimes to mixing criteria: Insights into high‐density binary particle systems

Y. X. Zhang, Lei Zhang, Shuyue Li, Zhihong Mao
article en

Abstract

Abstract A validated coarse‐grained computational fluid dynamics ‐ discrete element method (CFD‐DEM) framework is developed to investigate the flow and mixing behavior of ultra‐high‐density particles (6700–10,960 kg/m 3 ), far exceeding the density of conventional fluidization studies. Results show that the increases in a two‐segment fashion with density, deviating from classical predictions in the ultra‐dense regime. Despite low Archimedes numbers (9–15) predicting Group A classification, pressure fluctuation and bed expansion characteristics reveal a transition from Group B toward D behavior, demonstrating classification breakdown at extreme densities. For binary mixtures, pressure‐drop standard deviation serves as a dual diagnostic for both flow regimes and mixing states. Macroscopic mixing requires , with thresholds scaling nearly linearly with . Notably, systems with small density contrast achieve mixing more readily, even at higher absolute density. These findings provide a predictive framework for high‐density reactor design in nuclear‐fuel conversion.

AIChE Journal
China University of Petroleum, Beijing (CN)
Affordable and clean energy
Openalex Percentile: Top 44%
Granular flow and fluidized beds
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