A pressure correction method for fluid-particle interaction flow: Direct-forcing method and sedimentation flow

2010 ◽  
Vol 67 (12) ◽  
pp. 1771-1798 ◽  
Author(s):  
San-Yih Lin ◽  
Ya-Hsien Chin ◽  
Jeu-Jiun Hu ◽  
Yi-Cheng Chen
Author(s):  
Takeshi Seta

We demonstrate the applicability of the immersed boundary lattice Boltzmann method (IB-LBM) based on the implicit correction method to the simulation of rigid body motion in a viscous fluid and to the natural convection calculation. We compare the accuracy of the IB-LBM based on the implicit correction method with one of the IB-LBM based on the direct forcing method that eliminates the necessity of the determination of free parameters. In the simulations of the cylindrical Couette flow and of the heat transfer between two concentric cylinders, the implicit correction method indicates the first-order accuracy in the number of Lagrangian points. The accuracy of the IB-LBM based on the direct forcing method is independent of the number of the boundary points. The IB-LBM based on the implicit correction method is more accurate than one based on the direct forcing method.


Author(s):  
San-Yih Lin ◽  
Ya-Hsien Chin ◽  
Yi-Cheng Chen

A pressure correction method is developed to simulate fluid-particle interaction flows. In this Paper, the three-dimensional solid-fluid mixture flows are investigated. The pressure corrected method coupled with the direct-forcing immersed boundary (IB) and the volume of fluid (VOF) methods is used to simulate the mixture flows. A discrete element method (DEM) together with a multi-time-step algorithm is introduced into the pressure correction method to calculate the forces and torques between solid bodies and between solid bodies and walls. As a demonstration of the efficient and capabilities of the present method, four test cases are simulated. They include sedimentation of one spherical particle in an enclosure, collapse of six solid-cylinder layers, two-dimensional solid-fluid mixture flow, and three-dimensional solid-fluid mixture flow.


2021 ◽  
Author(s):  
Cindy Tran

The mixing quality of a solid-liquid stirred tank operating in the turbulent regime was investigated, numerically and to an extent experimentally. Simulations were performed by coupling Computational Fluid Dynamics (CFD) and the Discrete Element Method (DEM). The results were evaluated against experimental data obtained using Electrical Resistance Tomography (ERT). This facilitated a novel and more rigorous assessment of CFD-DEM coupling – i.e. based on the spatial distribution of particle concentrations. Furthermore, a new mixing index definition was developed to quantify suspension quality to work in tandem with existing dispersion mixing indexes. This provides a more complete interpretation of mixing quality. In this work, it was found that the model underestimated suspension and dispersion due to model limitations associated with mesh size and fluid-particle interaction models. Furthermore, the predicted mixing quality was sensitive to changes in the drag model, including other fluid-particle interaction forces in simulations, and variations in certain particle properties


2021 ◽  
Author(s):  
Cindy Tran

The mixing quality of a solid-liquid stirred tank operating in the turbulent regime was investigated, numerically and to an extent experimentally. Simulations were performed by coupling Computational Fluid Dynamics (CFD) and the Discrete Element Method (DEM). The results were evaluated against experimental data obtained using Electrical Resistance Tomography (ERT). This facilitated a novel and more rigorous assessment of CFD-DEM coupling – i.e. based on the spatial distribution of particle concentrations. Furthermore, a new mixing index definition was developed to quantify suspension quality to work in tandem with existing dispersion mixing indexes. This provides a more complete interpretation of mixing quality. In this work, it was found that the model underestimated suspension and dispersion due to model limitations associated with mesh size and fluid-particle interaction models. Furthermore, the predicted mixing quality was sensitive to changes in the drag model, including other fluid-particle interaction forces in simulations, and variations in certain particle properties


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