Modelling the Multiphase Flow in Dense Medium Cyclones

Chu, Kaiwei; Wang, Bo; Yu, Aibing; Vince, Andrew

doi:10.1260/1757-482x.2.4.249

Cited by 10 publications

(3 citation statements)

References 46 publications

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“…Obtained mathematical formulas for CFD-DEM method from literature [23]. The CFD-DEM coupling method consists of equations for controlling particle rotational motion and translation, Navier Stokes equations, and continuity equations for mass conservation [24]. Due to the bridging mechanism between particles on the screen of the spiral step cleaning device, an adhesion model based on Johnson Kendall Roberts (JKR) theory was used [25].…”

Section: Mathematical Methodsmentioning

confidence: 99%

Vortex Cleaning Device for Rice Harvester: Design and Bench Test

Liu,

Zeng,

Chen

2024

Agriculture

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To solve the problem of increased grain impurity rate and grain loss rate caused by clogging of sieve holes during the cleaning process of ratooning rice, a spiral step cleaning device was designed, which disturbed the flow field at the sieve holes through vortex in the slot and disrupted the force balance of the blockages at the sieve holes. The device mainly includes a cleaning separation core and a cleaning separation core shell. Firstly, the main parameters of the cleaning separation core were determined, and the critical shear airflow velocity was obtained through theoretical analysis. Through energy loss analysis, the fan wind speed was determined to be 11.5 m/s. Secondly, the CFD-DEM coupling method was used to analyze the flow patterns inside the slot and the movement patterns of blockages on the sieve surface, confirming the effectiveness of vortex guided blockage removal. Finally, a prototype was designed and built for testing, and the results showed that when the wind speed of the fan was 11.5 m/s, the grain impurity rate was 1.35%, the grain loss rate was 2.13%, and the average sieve blockage rate was ≤0.1%. All indicators were better than traditional cleaning devices and could meet the cleaning requirements. During the continuous operation of the spiral step cleaning device, performance indicators such as sieve hole blockage rate remained basically unchanged.

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Section: Mathematical Methodsmentioning

confidence: 99%

Vortex Cleaning Device for Rice Harvester: Design and Bench Test

Liu,

Zeng,

Chen

2024

Agriculture

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“…Processes 2020, 8, x FOR PEER REVIEW 2 of 12 simultaneously collected real-time raw coal information, product information, and suspension density data are not correlated with each other, and a large time-lag exists [4][5][6][7]. Recent studies about the dense medium separation have focused on the flow characteristics in the separator, especially on the influence of operating parameters, structural parameters, and flow field on the separation efficiency [8][9][10][11][12]. In terms of suspension density prediction, some scholars have studied the relationship between raw coal ash and suspension density to predict real-time density [10][11][12][13].…”

Section: Processmentioning

confidence: 99%

Prediction Model of Suspension Density in the Dense Medium Separation System Based on LSTM

et al. 2020

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In the dense medium separation system of coal preparation plant, the fluctuation of raw coal ash and lag of suspension density adjustment often causes the instability of product quality. To solve this problem, this study established a suspension density prediction model for the dense medium separation system based on Long Short-Term Memory (LSTM). First, the historical data in the dense medium separation system of a coal preparation plant were collected and preprocessed. Moving average and cubic exponential smoothing methods were used to replace abnormal data and to fill in the missing data, respectively. Second, a LSTM network was used to construct the density prediction model, and the optimal number of time steps, hidden layers, and nodes was determined. Finally, the model was employed on a testing set for prediction, and a Back-Propagation (BP) network without a time series was used for comparison. Root Mean Squared Error (RMSE) were the minimum when the number of the hidden layers, nodes, and time steps was 6, 12, and 5, respectively. In this case, the RMSE and Mean Absolute Percent Error (MAPE) of the LSTM method were 0.009 and 0.007, respectively, while those of the BP method were 0.019 and 0.015, respectively. Therefore, the model established using LSTM can be used to accurately predict the suspension density of the dense medium separation system.

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“…In the simulation of cyclone separators, the particle size, density, and inlet velocity must be taken into account. Chu et al 3 simulated the medium-coal flow in a dense medium cyclone (DMC) with the use of different models, such as CFD-LPT, CFD-DEM, the one-way coupling, CFD-DEM two-way coupling with parcel particles concept, and CFD-DEM two-way coupling models. They discuss the CFD-DEM one-way coupling model and consider particle-particle interaction on the base of CFD-LPT model and ignores the reaction of particles on fluid.…”

Section: Introductionmentioning

confidence: 99%

Effect of particle diameter and injection position on the separation performance of cyclone separators

Liu

Dou

Chen

2016

The Journal of Computational Multiphase Flows

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Effects of the particle diameter and particle injection position on the gas-solid two-phase flow have important implications in the tangential inlet cyclone separator. The Navier-Stokes equation coupled with the Reynolds stress model in Euler coordinate system is adopted to describe the gas flow and the discrete phase model in Lagrange coordinate system is used to calculate the particle trajectories. Results show that the separation efficiency varies with the injection position at the inlet cross-section. It is found that the separation efficiency is increased with the increase of the particle diameter. However, when the particle diameter exceeds a critical size, the particles will deposit on the wall of the conical chamber, which leads to lower separation efficiency. The present simulation indicates that the critical size is 24 mm.

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Modelling the Multiphase Flow in Dense Medium Cyclones

Cited by 10 publications

References 46 publications

Vortex Cleaning Device for Rice Harvester: Design and Bench Test

Vortex Cleaning Device for Rice Harvester: Design and Bench Test

Prediction Model of Suspension Density in the Dense Medium Separation System Based on LSTM

Effect of particle diameter and injection position on the separation performance of cyclone separators

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