Numerical simulation of near-gravity coal particle behavior in a dense medium cyclone using a mixture model coupled with a discrete phase model

2018 ◽  
pp. 1-23 ◽  
Author(s):  
Veera Asha Kumari Aketi ◽  
Vakamalla Teja Reddy ◽  
Narasimha Mangadoddy ◽  
Sreedhar G E ◽  
Shiva Kumar Raparla ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Mixture Model ◽  
Coal Particle ◽  
Phase Model ◽  
Dense Medium ◽  
Discrete Phase Model ◽  
Particle Behavior ◽  
Discrete Phase ◽  
Dense Medium Cyclone

scholarly journals Computational Fluid Dynamic study on the effect of near gravity material on dense medium cyclone treating coal using Discrete Phase Model and Algebraic Slip mixture multiphase model

2016 ◽  
Vol 9 (2) ◽  
pp. 58-70 ◽  
Author(s):  
Veera AK Aketi ◽  
TR Vakamalla ◽  
M Narasimha ◽  
GE Sreedhar ◽  
R Shivakumar ◽  
...  
Keyword(s):  
Coal Particle ◽  
Fluid Dynamic ◽  
Phase Model ◽  
Dense Medium ◽  
Multiphase Model ◽  
Discrete Phase Model ◽  
Mixture Density ◽  
Coal Particles ◽  
Discrete Phase ◽  
Dense Medium Cyclone

In this paper, the effect of near gravity material at desired separation density during the coal washing is studied. It is believed that the Dense Medium Separation of coal particles in the presence of high percentage of near gravity material, results in a significant misplacement of coal particles to wrong products. However the performance of dense medium cyclone does not merely depend on the total amount of near gravity materials but also on their distribution as well as on their quality. This paper deals with numerical simulation of magnetite medium segregation and coal partitioning handled in a 350 mm dense medium cyclone. Volume of Fluid coupled with Reynolds Stress Model is used to resolve the two-phase air-core and turbulence. Algebraic Slip mixture multiphase model with the granular options are considered to predict magnetite medium segregation. Medium segregation results are validated against Gamma Ray Tomography measurements. Further, Discrete Phase Model is used to track the coal particles. Residence Time Distribution of different size and density coal particles are also estimated using Discrete Phase Model. Additionally, Algebraic Slip mixture model is also utilised to simulate magnetite and coal particle segregation at different near gravity material proportions. Discrepancies in the coal particle behaviour at different near gravity material content are explained using locus of zero vertical velocities, mixture density, coal volume fractions.

Numerical simulation of circulating fluidized bed oxy-fuel combustion with Dense Discrete Phase Model

2019 ◽  
Vol 195 ◽  
pp. 106129 ◽  
Author(s):  
Ying Wu ◽  
Daoyin Liu ◽  
Dong Zheng ◽  
Jiliang Ma ◽  
Lunbo Duan ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Fluidized Bed ◽  
Circulating Fluidized Bed ◽  
Fuel Combustion ◽  
Phase Model ◽  
Discrete Phase Model ◽  
Discrete Phase

scholarly journals Enhanced discrete phase model for multiphase flow simulation of blood flow with high shear stress

2021 ◽  
Vol 104 (1) ◽  
pp. 003685042110080
Author(s):  
Zheqin Yu ◽  
Jianping Tan ◽  
Shuai Wang
Keyword(s):  
Blood Flow ◽  
Shear Stress ◽  
Multiphase Flow ◽  
Experimental Verification ◽  
Flow Simulation ◽  
Turbulence Models ◽  
Phase Model ◽  
Force Model ◽  
Discrete Phase Model ◽  
Discrete Phase

Shear stress is often present in the blood flow within blood-contacting devices, which is the leading cause of hemolysis. However, the simulation method for blood flow with shear stress is still not perfect, especially the multiphase flow model and experimental verification. In this regard, this study proposes an enhanced discrete phase model for multiphase flow simulation of blood flow with shear stress. This simulation is based on the discrete phase model (DPM). According to the multiphase flow characteristics of blood, a virtual mass force model and a pressure gradient influence model are added to the calculation of cell particle motion. In the experimental verification, nozzle models were designed to simulate the flow with shear stress, varying the degree of shear stress through different nozzle sizes. The microscopic flow was measured by the Particle Image Velocimetry (PIV) experimental method. The comparison of the turbulence models and the verification of the simulation accuracy were carried out based on the experimental results. The result demonstrates that the simulation effect of the SST k- ω model is better than other standard turbulence models. Accuracy analysis proves that the simulation results are accurate and can capture the movement of cell-level particles in the flow with shear stress. The results of the research are conducive to obtaining accurate and comprehensive analysis results in the equipment development phase.

A numerical study of snow accumulation on the bogies of high-speed trains based on coupling improved delayed detached eddy simulation and discrete phase model

2018 ◽  
Vol 233 (7) ◽  
pp. 715-730 ◽  
Author(s):  
Mingyang Liu ◽  
Jiabin Wang ◽  
Huifen Zhu ◽  
Sinisa Krajnovic ◽  
Guangjun Gao
Keyword(s):  
High Speed ◽  
Numerical Study ◽  
Snow Accumulation ◽  
Phase Model ◽  
Detached Eddy Simulation ◽  
Discrete Phase Model ◽  
Eddy Simulation ◽  
Delayed Detached Eddy Simulation ◽  
Flow Mechanisms ◽  
Discrete Phase

A numerical simulation method based on the improved delayed detached eddy simulation coupled with a discrete phase model is used to study the influence of the snow on the performance of bogies of a high-speed train running in snowy weather. The snow particle trajectories, mass of snow packing on the bogie, and thickness of snow accumulation have been analyzed to investigate the flow mechanisms of snow accumulation on different parts of the bogies. The results show that the snow accumulation on the first bogie of the head vehicle is almost the same as that of the second bogie, but the total accumulated snow on the top side of the second bogie is more than 74% higher than that of the first bogie. Among all the components of the bogies, the motors were found to be strongly influenced by the snow accumulation. The underlying flow mechanisms responsible for the snow accumulations are discussed.

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