Implementation issues and benchmarking of lattice Boltzmann method for moving rigid particle simulations in a viscous flow

Peng, Cheng; Teng, Yihua; Hwang, Brian Y.; Guo, Zhaoli; Wang, Lian‐Ping

doi:10.1016/j.camwa.2015.08.027

Cited by 84 publications

(92 citation statements)

References 54 publications

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“…It is clear that the GME results are more accurate and far steadier than the ALD and LME results. Peng et al [62] confirmed the computational accuracy and Galilean invariance of GME by theoretical analyses and numerical simulations. investigate the influences of Reynolds number, we perform a set of simulations in which the particle densities increase from 1.02 to 1.22 g/cm 3 , and the corresponding Reynolds number grows gradually from 6.13 to 34.75.…”

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confidence: 50%

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confidence: 50%

“…Peng et al [62] proposed a refill scheme by velocity-constrained normal extrapolation based on the multiple-relaxation-time LBM. After the missing distribution functions of a newborn fluid node are completed by the normal extrapolation refill scheme, all moments at the newborn node are computed by multiplying the transfer matrix M, m(x,t) " M¨f(x,t) (38) wheref indicates the temporary distribution functions.…”

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Hydrodynamic Force Evaluation by Momentum Exchange Method in Lattice Boltzmann Simulations

Wen

Zhang

Fang

2015

Entropy

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Abstract:As a native scheme to evaluate hydrodynamic force in the lattice Boltzmann method, the momentum exchange method has some excellent features, such as simplicity, accuracy, high efficiency and easy parallelization. Especially, it is independent of boundary geometry, preventing from solving the Navier-Stokes equations on complex boundary geometries in the boundary-integral methods. We review the origination and main developments of the momentum exchange method in lattice Boltzmann simulations. Then several practical techniques to fill newborn fluid nodes are discussed for the simulations of fluid-structure interactions. Finally, some representative applications show the wide applicability of the momentum exchange method, such as movements of rigid particles, interactions of deformation particles, particle suspensions in turbulent flow and multiphase flow, etc.

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Hydrodynamic Force Evaluation by Momentum Exchange Method in Lattice Boltzmann Simulations

Wen

Zhang

Fang

2015

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“…The missing distribution functions for the new fluid lattice node are constructed by a new velocityconstrained extrapolation method to be discussed below (section 2.2). The hydrodynamic force F i and torque Γ i acting on the i th particle are calculated during the interpolated bounce-back procedure by the recentlydeveloped Galiean invariant momentum exchange method [39,40]. It is very important that we enforce the local Galilean invariance property in order to produce physically correct results, as discussed in Peng et al [40].…”

Section: The Lattice Boltzmann Methods (Lbm)mentioning

confidence: 99%

Lattice Boltzmann simulation of particle-laden turbulent channel flow

et al. 2016

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Highlights• We present the first LBM simulations of particle-laden turbulent channel flows.• The results of single-phase flow are in excellent agreement with benchmark data.• The LBM results of particle-laden flow are similar to finite-difference results.• The presence of particles is shown to significantly alter flow statistics.• The nature of flow modulation depends on spatial location relative to the walls. AbstractModulation of the carrier phase turbulence by finite-size solid particles is relevant to many industrial and environmental applications. Here we report particle-resolved simulations of a turbulent channel flow laden with finite-size solid particles. We discuss how the mesoscopic lattice Boltzmann method (LBM) can be applied to treat both the turbulent carrier flow and moving fluid-particle interfaces. To validate the LBM approach, we first simulate the single-phase turbulent channel flow at a frictional Reynolds number of 180. A non-uniform force field is designed to excite turbulent fluctuations. The resulting mean flow profiles and turbulence statistics were found to be in excellent agreement with the published data based on the Chebychev-spectral method. We also found that the statistics of the fully-developed turbulent channel flow are independent of the setting of some of the relaxation parameters in the LBM approach. We then consider a particle-laden turbulent channel flow under the same body force. The particles have the same density as the fluid. The particle diameter is 5% of the channel width and the average volume fraction is 7.09%. We found that the presence of the particles reduces the mean flow speed by 4.6%, implying that the fluid-particle system is more dissipative than the single-phase flow. The maximum local reduction of the mean flow speed is about 7.5%. The effects of the solid particles on the fluid r.m.s. velocity fluctuations are mixed: both reduction and augmentation are observed depending on the direction and spatial location relative to the channel walls. Overall, particles enhance the relative turbulence intensity in the near wall region and suppress the turbulence intensity in the center region. The particle concentration distribution across the channel is also complicated. We find that there is a dynamic equilibrium location resembling the Segŕe-Silberberg effect known for a laminar wall-bounded flows. Our LBM results were found to be in good agreement with results based on a finite-difference method with direct forcing to handle the moving solid particles. Additionally, phase-partitioned statistics are obtained and compared.

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“…This then requires the restoring of the missing distribution functions f q , which can be achieved by setting them to their equilibrium value based on a local average density or by extrapolating them from the body's normal direction, see e.g. [4]. All restoration algorithms must satisfy the constraint that the fluid velocity in these cells has to match the body's surface velocity at this position.…”

Section: Numerical Algorithmmentioning

confidence: 99%

Simulations of Particle‐laden Flows with the Lattice Boltzmann Method

Rettinger

Rüde

2016

Proc Appl Math and Mech

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A lattice Boltzmann method is presented which enables the direct numerical simulation of particle-laden flows. It applies a fluid-solid coupling technique based on the momentum exchange method to represent geometrically fully resolved particles of arbitrary shape. The test case of a single moving sphere allows an in-depth evaluation of the algorithm. The method is fully parallelizable and yields results with an accuracy comparable to classical CFD simulations. This forms the basis for simulations of complex systems involving several thousand particles like the sediment transport in river beds. MotivationNumerical simulations have become an important tool to investigate particulate flows, like sediment transport in river beds or fluidization of particle beds. They are used to gain a better understanding of the behavior of such complex systems. To avoid empirical modeling assumptions, one has to resort to direct numerical simulations (DNS) with appropriate fluid-solid coupling algorithms. In computational fluid dynamics (CFD), the lattice Boltzmann method (LBM) has developed into a viable alternative to solve the Navier-Stokes equations numerically. Over the years, various algorithms have been developed for the DNS of particulate flows such as the immersed boundary method, Noble and Torczynski's immersed moving boundary method, and the momentum exchange method. The lattice Boltzmann method presented in this article is suitable for the accurate simulation of particle-laden flows on massively parallel supercomputers. Numerical AlgorithmLattice Boltzmann method: The LBM originates from statistical mechanics and models the evolution of distribution functions f q , corresponding to the lattice velocities c q , on a rectangular grid. Macroscopic quantities can be calculated via moments such as density ρ = q f q and momentum ρ u = q f q c q . By applying the BGK collision model, the evolution equation of the distribution functions readswhich models the linear relaxation of the f q towards their equilibrium values f eq q . The relaxation parameter τ determines the physical viscosity ν. For improved stability and accuracy, more enhanced models like TRT or MRT should be used which then feature several relaxation parameters, see e.g. [1]. Momentum exchange method: This fluid-solid coupling method (see [2]) maps the body explicitly into the domain by marking cells as solid rather than fluid. In order to fulfill the no-slip condition along the body's surface with a local velocity u p , the boundary conditionis applied at the boundary cells. This simple bounce-back scheme can be improved to account for the exact boundary location by schemes like Central Linear Interpolation (CLI) or Multireflection (MR) [1]. On the other hand, the fluid exerts a hydrodynamic force onto the body. For each boundary cell, the local contribution to this force acting at position x b is computed as in [3], taking special care of Galilean invariance, byThe total force and torque on the body is then obtained by summing up all local contributions. Toge...

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Implementation issues and benchmarking of lattice Boltzmann method for moving rigid particle simulations in a viscous flow

Cited by 84 publications

References 54 publications

Hydrodynamic Force Evaluation by Momentum Exchange Method in Lattice Boltzmann Simulations

Hydrodynamic Force Evaluation by Momentum Exchange Method in Lattice Boltzmann Simulations

Lattice Boltzmann simulation of particle-laden turbulent channel flow

Simulations of Particle‐laden Flows with the Lattice Boltzmann Method

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