Influence of void fraction calculation on fidelity of CFD‐DEM simulation of gas‐solid bubbling fluidized beds

Peng, Zhengbiao; Doroodchi, Elham; Luo, Caimao; Moghtaderi, Behdad

doi:10.1002/aic.14421

Cited by 269 publications

(117 citation statements)

References 75 publications

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“…It can be seen that when the particle centroid is located near cell boundaries (e.g., particle P2 in Fig. 1(a)), the error can be up to 50% (Peng et al, 2014). If a cell contains several such particles and if these particles are large compared to the host cell, unphysically large values can occur for this cell, leading to a non-smooth solid particle volume field with large gradients.…”

Section: Particle Centroid Methodsmentioning

confidence: 99%

Diffusion-based coarse graining in hybrid continuum–discrete solvers: Theoretical formulation and a priori tests

Sun

Xiao

2015

International Journal of Multiphase Flow

117

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Coarse graining is an important ingredient in many multi-scale continuum-discrete solvers such as CFD-DEM (computational fluid dynamics-discrete element method) solvers for dense particle-laden flows. Although CFD-DEM solvers have become a mature technique that is widely used in multiphase flow research and industrial flow simulations, a flexible and easy-to-implement coarse graining algorithm that can work with CFD solvers of arbitrary meshes is still lacking. In this work, we proposed a new a CFD-DEM solver, the results of which are presented in a separate work (R. Sun and H. Xiao, Diffusion-based coarse graining in hybrid continuum-discrete solvers:Application in CFD-DEM solvers for particle laden flows. International Journal of Multiphase Flow 72, 233247).

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Section: Particle Centroid Methodsmentioning

confidence: 99%

Diffusion-based coarse graining in hybrid continuum–discrete solvers: Theoretical formulation and a priori tests

Sun

Xiao

2015

International Journal of Multiphase Flow

117

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“…See text for discussion and Movie S1 for a full animation. Details of the calculation are found in the supporting information [Alizadeh et al, 2014;Coetzee and Els, 2009;Cole and Hopkins, 2016;Costa et al, 2010;Davidson et al, 2001;Li and Guenther, 2012;Nakamura and Watano, 2007;Paulick et al, 2015;Peng et al, 2014;Richter et al, 2003;Ruprecht et al, 2012;Tsuji et al, 1993;Wallace and Bergantz, 2005].…”

Section: Force Chainsmentioning

confidence: 99%

On the kinematics and dynamics of crystal‐rich systems

2017

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Partially molten rocks, often called a mush, are examples of a hydrogranular mixture where the dynamics are controlled by both fluid and crystal‐crystal interactions. An obstacle to progress in understanding high‐temperature hydrogranular systems has been the lack of adequate levels of description of microphysical processes. Here we rationalize the hydrogranular kinematic and dynamic states by applying the concept of particle (crystal) force chains. We exemplify this with discrete‐element computational fluid dynamic simulations of the intrusion of a basaltic melt into an olivine‐basalt mush, where crystal‐scale force chains, crystal transport, and melt mixing are resolved. To describe the microscale kinematics of the system, we introduce the coordination number and the fabric tensors of particle contacts and forces. We quantify the changing contact and force fabric anisotropy, coaxiality, and the connectedness of the mush, under dynamic conditions. To describe the dynamics, particle and fluid characteristic response times are derived. These are used to define local and bulk Stokes numbers, and viscous and inertia numbers, which quantify the multiphase coupling under crystal‐rich conditions. We employ the Sommerfeld number, which describes the importance of crystal‐melt lubrication, with a viscous number to illustrate the dynamic regimes of crystal‐rich magmas. We show that the notion of mechanical “lock up” is not uniquely identified with a particular crystal volume fraction and that distinct mechanical behaviors can emerge simultaneously within a crystal‐rich system. We also posit that this framework describes magmatic fabrics and processes which “unlock” a crystal mush prior to eruption or mixing.

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“…Other detailed simulation parameters are listed in Table 4. 42,43 For coarse DEM simulations, the smaller parcel to grid size ratio of 2 allows for a sufficient number of grid cells to resolve the fluid flow since fewer cells are used as parcels become coarser. For CFD-DEM simulations, the CFD grid size is set to 4 d p .…”

Section: Equations Of Motion For Particlesmentioning

confidence: 99%

“…This will reduce the computational cost with little influence on the simulation results since both grid sizes are sufficiently fine to resolve most flow structures. 42,43 For coarse DEM simulations, the smaller parcel to grid size ratio of 2 allows for a sufficient number of grid cells to resolve the fluid flow since fewer cells are used as parcels become coarser.…”

Section: Equations Of Motion For Particlesmentioning

confidence: 99%

Method to estimate uncertainty associated with parcel size in coarse discrete particle simulation

Benyahia

2018

AIChE Journal

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Coarse grained particle methods significantly reduce the computation cost of large‐scale fluidized bed simulation by lumping many real particles into a computation parcel. This research provides a method to estimate the errors associated with parcel size in large‐scale fluidized bed simulations. This uncertainty is first quantified in small scale domains by comparing results of discrete particle method with that employing coarse parcels of different sizes. Then, this uncertainty is correlated with parcel size and simulation domains consisting of a simple homogeneous cooling system and more complex bubbling and circulating fluidized beds. These correlations allow us to accurately estimate the uncertainty in large‐scale fluidized beds based solely on data obtained in smaller systems. The ability to estimate model‐related uncertainty in larger systems makes this method relevant for industrial applications. © 2018 American Institute of Chemical Engineers AIChE J, 64: 2340–2350, 2018

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Influence of void fraction calculation on fidelity of CFD‐DEM simulation of gas‐solid bubbling fluidized beds

Cited by 269 publications

References 75 publications

Diffusion-based coarse graining in hybrid continuum–discrete solvers: Theoretical formulation and a priori tests

Diffusion-based coarse graining in hybrid continuum–discrete solvers: Theoretical formulation and a priori tests

On the kinematics and dynamics of crystal‐rich systems

Method to estimate uncertainty associated with parcel size in coarse discrete particle simulation

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