Particle-Resolved Direct Numerical Simulation for Gas-Solid Flow Model Development

Tenneti, Sudheer; Subramaniam, Shankar

doi:10.1146/annurev-fluid-010313-141344

Cited by 287 publications

(135 citation statements)

References 99 publications

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“…Resolved particle direct numerical simulations of particulate flows have been developing last two decades (see the review of Tenetti and Subramanian, 2014 ). These simulations can provide the particulate phase fluctuation characteristics in order to develop appropriate two-phase continuum models.…”

Section: Introductionmentioning

confidence: 99%

Particle resolved direct numerical simulation of a liquid–solid fluidized bed: Comparison with experimental data

Özel

Motta

Abbas

et al. 2017

International Journal of Multiphase Flow

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao. (10), respectively. In this paper, we compare the statistical quantities computed from numerical results with the experimental data obtained with 3-D trajectography and High Frequency PIV. Fluidization law predicted by the numerical simulations is in very good agreement with the experimental curve and the main features of trajectories and Lagrangian velocity signal of the particles are well reproduced by the simulations. The evolution of particle and flow velocity variances as a function of bed solid volume fraction is also well captured by the simulations. In particular, the numerical simulations predict the right level of anisotropy of the dispersed phase fluctuations and its independence of bed solid volume fraction. They also confirm the high value of the ratio between the fluid and the particle phase fluctuating kinetic energy. A quick analysis suggests that the fluid velocity fluctuations are mainly driven by fluid-particle wake interactions (pseudo-turbulence) whereas the particle velocity fluctuations derive essentially from the large scale flow motion (recirculation). Lagrangian autocorrelation function of particle fluctuating velocity exhibits large-scale oscillations, which are not observed in the corresponding experimental curves, a difference probably due to a statistical averaging effect. Evolution as a function of the bed solid volume fraction and the collision frequency based upon transverse component of particle kinetic energy correctly matches the experimental trend and is well fitted by a theoretical expression derived from Kinetic Theory of Granular Flows.

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Section: Introductionmentioning

confidence: 99%

Particle resolved direct numerical simulation of a liquid–solid fluidized bed: Comparison with experimental data

Özel

Motta

Abbas

et al. 2017

International Journal of Multiphase Flow

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“…Types of flows Re p Kim and Balachandar (2012) An isolated finite-sized particle subjected to isotropic turbulent cross-flow 100, 250, 350 Zeng et al (2010) A finite-sized stationary particle in a channel flow of modest turbulence 40 ∼ 450 Lucci et al (2010) Finite-sized solid spherical particles in decaying isotropic turbulence O (10) (65/75/280) Belt et al (2012) Particle-laden secondary flow in turbulent pipe flows 110, 217 Xu and Bodenschatz (2008) Particles in intense turbulent water flows 22, 35, 55 Kidanemariam et al (2013) Horizontal open channel flow with finite-size, heavy particles 15 ∼ 20 Laín and Sommerfeld (2012) Pneumatic conveying of spherical particles in horizontal ducts 40 Dorgan and Loth (2004) Particles released near the wall in a turbulent boundary layer 10 −5 ∼ 30 Zeng et al (2008) Turbulent channel flow over an isolated particle of finite-size 42 ∼ 295, 325/455 Tenneti and Subramaniam (2014) Gas-solid flows 20, 50 Wang et al (2008) Sedimentation of 1, 2 or 105 particles in a channel flow about 17.3, 503 García-Villalba et al (2012) Vertical plane channel flow with finite-size particles 132 Uhlmann (2008) Vertical particulate channel flow 136 Uhlmann and Doychev (2014) The gravity-induced motion of randomly distributed, finite-size, heavy particles in quiescent fluid in triply periodic domains ing on a sphere near the wall and experimentally study translational and rotational motion of a particle slightly heavier than the fluid in a rotating drum filled with water. Lin and Lin (2013) numerically studied the effects of finite particle Reynolds numbers up to Re p = 50 on the model for normal lubrication force on a particle moving towards a solid wall using the immersed boundary method.…”

Section: Referencesmentioning

confidence: 99%

Hydrodynamic force and torque models for a particle moving near a wall at finite particle Reynolds numbers

Zhou

Jin

Tian

et al. 2017

International Journal of Multiphase Flow

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: Models for hydrodynamic force and torque Finite particle Reynolds number Near-wall effect Particle-resolved simulation Sub-grid scale model Eulerian-Lagrangian simulation a b s t r a c t This research work is aimed at proposing models for the hydrodynamic force and torque experienced by a spherical particle moving near a solid wall in a viscous fluid at finite particle Reynolds numbers. Conventional lubrication theory was developed based on the theory of Stokes flow around the particle at vanishing particle Reynolds number. In order to account for the effects of finite particle Reynolds number on the models for hydrodynamic force and torque near a wall, we use four types of simple motions at different particle Reynolds numbers. Using the lattice Boltzmann method and considering the moving boundary conditions, we fully resolve the flow field near the particle and obtain the models for hydrodynamic force and torque as functions of particle Reynolds number and the dimensionless gap between the particle and the wall. The resolution is up to 50 grids per particle diameter. After comparing numerical results of the coefficients with conventional results based on Stokes flow, we propose new models for hydrodynamic force and torque at different particle Reynolds numbers. It is shown that the particle Reynolds number has a significant impact on the models for hydrodynamic force and torque. Furthermore, the models are validated against general motions of a particle and available modeling results from literature. The proposed models could be used as sub-grid scale models where the flows between particle and wall can not be fully resolved, or be used in Lagrangian simulations of particle-laden flows when particles are close to a wall instead of the currently used models for an isolated particle.

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“…Particle-resolved direct numerical simulation (PR-DNS) is an alternative approach that is well suited for discovering flow physics in particle-laden flow (Tenneti and Subramaniam, 2014). The PR-DNS approach not only provides detailed information about the hydrodynamic velocity and pressure fields, it also provides particles trajectories along with their velocities and accelerations.…”

Section: Introductionmentioning

confidence: 99%

Development of a gas–solid drag law for clustered particles using particle-resolved direct numerical simulation

Mehrabadi

Murphy

Subramaniam

2016

Chemical Engineering Science

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Particle-resolved direct numerical simulation (PR-DNS) is used to quantify the drag force on clustered particle configurations over the solid phase volume fraction range of 0.1 ≤ φ ≤ 0.35 and the mean slip Reynolds number range of 0.01 ≤ Re m ≤ 50. The particle configurations and flow parameters correspond to gas-solid suspensions of Geldart A particles in which formation of clusters have been reported. In our PR-DNS, we use clustered particle configurations that match cluster statistics observed in experimental studies.To generate the particle configurations, we perform discrete element method (DEM) simulations of homogeneous cooling gas (HCG) systems with cohesive and inelastic particles in the absence interstitial fluid. Clustered particle subensembles are then extracted from HCG simulations to match the statistics of cluster size distributions observed in experiments. These sub-ensembles are used for PR-DNS. It is found that the mean drag on clustered configurations decreases when compared to the drag laws for uniform particle configura- * tions. The maximum drag reduction belongs to the configuration with low solid-phase volume fraction φ = 0.1 in Stokes flow, and is about 35%. The drag reduction reduces with increase in both φ and Re m . A clustering metric is introduced to explain the behavior of the drag reduction with respect to solid-phase volume fraction. Also the behavior of the drag reduction with mean slip Reynolds number is related to the Brinkman screening length. PR-DNS results are then used to propose a clustered drag model for the range of flow parameters considered in this study. This clustered drag model provides a smooth transition between the uniform and clustered states by means of a weighting function with two model parameters.

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Particle-Resolved Direct Numerical Simulation for Gas-Solid Flow Model Development

Cited by 287 publications

References 99 publications

Particle resolved direct numerical simulation of a liquid–solid fluidized bed: Comparison with experimental data

Particle resolved direct numerical simulation of a liquid–solid fluidized bed: Comparison with experimental data

Hydrodynamic force and torque models for a particle moving near a wall at finite particle Reynolds numbers

Development of a gas–solid drag law for clustered particles using particle-resolved direct numerical simulation

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