Research on Impurity Separation Behavior During Pre-Storage Paddy Cleaning with CFD-DPM

Paddy grains require impurity removal before storage, and cyclone air separation is the final stage for removing lightweight impurities. In this study, a three-dimensional computational fluid dynamics–discrete phase model (CFD–DPM) was established to investigate impurity separation in a cyclone air separation device. The Reynolds stress model (RSM) was used for the continuous air phase, and the discrete phase model (DPM) was used to track impurity particles. Simulations were performed at an inlet velocity of 9 m/s, corresponding to a Reynolds number (Re) of approximately 1.84 × 105 based on an inlet hydraulic diameter of 0.299 m. Three structural parameters were investigated: the dust outlet diameter (Ddo = 454–654 mm), conical section length (Lcs = 1476–1876 mm), and impurity capture diameter (Dic = 240–440 mm). Particle tracking showed four main stages: particle entry, downward spiral motion, size-dependent separation, and discharge. When Ddo increased from 454 to 654 mm, separation efficiency decreased from 88.75% to 55.46%, while the pressure drop decreased from 223.65 to 161.09 Pa. Increasing Lcs from 1476 to 1876 mm increased the separation efficiency from 44.46% to 82.87%, with the pressure drop increasing from 170.13 to 208.90 Pa. Increasing Dic from 240 to 440 mm reduced the separation efficiency from about 85% to 53%, while the pressure drop decreased from about 205 to 173 Pa. These results show that the structural parameters affect separation performance by changing the swirling flow and particle migration path.

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Publication Details

Journal
Processes
Published
2026-11-03
DOI
https://doi.org/10.3390/pr14213545
Primary Topic
Cyclone Separators and Fluid Dynamics
Type
article
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article

Research on Impurity Separation Behavior During Pre-Storage Paddy Cleaning with CFD-DPM

Can Shu, Liu Qing Yang, Dong Yang, Nianwu Wei et al.
Processes
Cyclone Separators and Fluid Dynamics
article

Research on Impurity Separation Behavior During Pre-Storage Paddy Cleaning with CFD-DPM

Can Shu, Liu Qing Yang, Dong Yang, Nianwu Wei, Xinfeng Hu, Zhiqi Hou, Menghao Zhao
article en

Abstract

Paddy grains require impurity removal before storage, and cyclone air separation is the final stage for removing lightweight impurities. In this study, a three-dimensional computational fluid dynamics–discrete phase model (CFD–DPM) was established to investigate impurity separation in a cyclone air separation device. The Reynolds stress model (RSM) was used for the continuous air phase, and the discrete phase model (DPM) was used to track impurity particles. Simulations were performed at an inlet velocity of 9 m/s, corresponding to a Reynolds number (Re) of approximately 1.84 × 105 based on an inlet hydraulic diameter of 0.299 m. Three structural parameters were investigated: the dust outlet diameter (Ddo = 454–654 mm), conical section length (Lcs = 1476–1876 mm), and impurity capture diameter (Dic = 240–440 mm). Particle tracking showed four main stages: particle entry, downward spiral motion, size-dependent separation, and discharge. When Ddo increased from 454 to 654 mm, separation efficiency decreased from 88.75% to 55.46%, while the pressure drop decreased from 223.65 to 161.09 Pa. Increasing Lcs from 1476 to 1876 mm increased the separation efficiency from 44.46% to 82.87%, with the pressure drop increasing from 170.13 to 208.90 Pa. Increasing Dic from 240 to 440 mm reduced the separation efficiency from about 85% to 53%, while the pressure drop decreased from about 205 to 173 Pa. These results show that the structural parameters affect separation performance by changing the swirling flow and particle migration path.

ProcessesVol. 14(21)
Wuhan Polytechnic University (CN), Hong Kong University of Science and Technology (HK), Dongfeng Motor Group (China) (CN)
Openalex Percentile: Top 21%
Cyclone Separators and Fluid Dynamics
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Research on Impurity Separation Behavior During Pre-Storage Paddy Cleaning with CFD-DPM — Can Shu, Liu Qing Yang, et al. · Processes (2026) | TGRS Research Map | TGRS