An Open Source CFD-DEM Perspective

An Open Source CFD-DEM Perspective 

Christoph Goniva 

Christoph Kloss 

Alice Hager 

Stefan Pirker 

Christian Doppler Laboratory on Particulate Flow Modelling 

Johannes Kepler University Linz 

www.cfdem.com | www.particule-flow.at

An Open Source CFD – DEM Perspective 

Contents 

1. Introduction of the Laboratory 

2. Motivation 

3. The Open Source code LIGGGHTS / LAMMPS 

4. CFD – DEM coupling 

5. Validation example 

www.cfdem.com 

CD-Laboratory on Particulate Flow Modelling 

www.particulate-flow.at


Introduction of the lab 

Founded in 2009 by Dr. Stefan Pirker at the 

Johannes Kepler University, Linz, Austria. 

Governmental funding (50-70%) for application 

oriented fundamental research based on existing 

knowledge on particulate flows at the Institute of 

Fluid Mechanics and Heat Transfer of the JKU. 

Our research focus covers: 

(a) solids charging, 

(b) offgas scrubbing, 

(c) industrial dust recycling, 

(d) sedimentation & erosion and 

(e) trickling beds 

Current Industrial partners: 

Siemens VAI Metals Technologies, 

voestalpine Stahl, 

voestalpine Donawitz, 

Polysius (ThyssenKrupp group) 

www.cfdem.com 


www.particulate-flow.at 

3


Introduction of the lab 

CD-Laboratory on 

Particulate Flow Modelling 

Industrial Partners 

Offgas Scrubbing 

Solids Charging 

Industrial Dust Recycling 

Associated research 

Sedimentation & Erosion 

Tickling Bed 

www.cfdem.com 


www.particulate-flow.at


Motivation 

Many applications require coupled CFD-DEM simulations ! 

Unfortunately, the CFD-DEM Approach is CPU intensive … 

An efficient CFD-DEM solver is on need 

‣ Fast solver (both CFD and DEM) 

‣ Efficient parallelisation 

‣ Low license fees 

‣ Open access to source code 

‣ GPU acceleration for DEM is desirable to handle industrial scale processes 

OpenFoam is already established as leading Open Source CFD toolbox… 

LIGGGHTS is a parallel efficient DEM solver 

www.cfdem.com CD-Laboratory on Particulate Flow Modelling www.particulate-flow.at 

5


LAMMPS / LIGGGHTS 

LAMMPS = 

Large Atomic and Molecular Massively Parallel Simulator 

OpenSource under GPL, provided by Sandia National Laboratories since the 

mid 90‘s (http://lammps.sandia.gov/) 

Widely used (over 500 journal publications 2000-2009 using LAMMPS) 

see http://lammps.sandia.gov/papers.html 

LAMMPS has potentials for soft materials (biomolecules, polymers), solid-state 

materials (metals, semiconductors) and coarse-grained systems. It can be used 

to model atoms or, more generically, as a parallel particle simulator at the 

atomic, meso, or continuum scale. 

LAMMPS is a C++ code, it runs on single processors or in parallel using messagepassing 

techniques and a spatial-decomposition of the simulation domain. 

The code is designed to be easy to modify or extend with new functionality. 

It is very fast and also used on huge clusters (e.g. on Sandia Red Storm with 16k 

Quadcore nodes, simulations with 2 billion particles performed) 


6



Currently, LAMMPS offers a fast and efficient “GRANULAR” package for 

doing DEM simulations. Thereby, we profit from the fact that there are physical 

and algorithmic analogies between DEM and MD 

The key functionalities of this LAMMPS package are: 

‣ Pairwise interaction styles: Hooke and Hertz contact laws 

with optional friction 

‣ Granular walls: (Hooke and Hertz, with optional friction) for 

geometric primitives (box, cylinder) 

‣ Shear history for pairwise interaction and granular walls 


7



The key functionalities of this package are (continued): 

‣ A function to insert/pour a stream of material into a 

geometrical region 

‣ Functions to introduce gravity , freeze particles 

and exert Stokes drag 

‣ Multibody dynamics which can be modified to use it 

for handling of non-spherical particles 

‣ With pair style “hybrid/overlay”, other LAMMPS functionalities can be 

added easily (e.g. adding bonds, point charges, dipole moments,...) 


8



LIGGGHTS application example: 


9



Goals of the CFDEM Project: 

‣ Creating a CFD-DEM framework for high performance computing 

‣ Make LAMMPS feasible for industrial applications 

LIGGGHTS = 

LAMMPS IMPROVED FOR GENERAL GRANULAR AND 

GRANULAR HEAT TRANSFER SIMULATIONS 

WWW.LIGGGHTS.COM | WWW.CFDEM.COM 


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The following challenges have been tackled with LIGGGHTS: 

Feature LAMMPS LIGGGHTS 1.0 

Complex wall import from CAD No Yes 

Improved pair style No Yes 

Moving mesh No Yes 

Pour nonspherical clumps 

(multisphere method) 

No 

Macroscopic cohesion model No Yes 

Heat transfer model No Yes 

In progress... 

Particle bonds with torques No In progress... 

Wall Stress Analysis No Yes 

6 dof solver No Yes 


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CFD – DEM coupling 

Theoretical background: 

f4 

f1 

f2 f3 

= + 

-(f1 + f2) 

αf,1 

αf,2 

-(f3 + f4) 

DEM with force on 

particles coming 

from CFD 

CFD with adapted 

voidfraction 

and momentum sources 

www.cfdem.com 



12




Navier-Stokes equations for the fluid in presence of a granular phase 

∂α 

∂ 

α f 

u f 

f 

∂ t 

ρ 

( α ρ u ) 

f 

f 

f 

∂ t 

f 

+ ∇ ⋅ 

( α ρ u ) 

f 

+ ∇ ⋅ 

f 

( α ρ u u ) p K ( u u ) ( ) 

f f 

= −α 

∇ − 

fs f 

− 

s 

+ ∇ ⋅ α τ + α ρ g 

f 

f 

= 

f 

0 

fluid volume fraction 

fluid velocity 

τ, p stress tensor, pressure 

fluid density 

ρ f 

K fs 

f 

fluid solid momentum exchange term 

comprises drag force, Magnus and Saffman force, virtual mass force,... 

f 

f 

f 

www.cfdem.com 



13




Example for fluid solid momentum exchange Kfs : 

Gidaspow (1992): Hydrodynamics of Circulating Fluidized Beds, Kinetic Theory Approach. In Fluidization 

VII, Proceedings of the 7 th Engineering Foundation Conference on Fluidization, pages 75‐82 

α f 

> 0.8: 

K 

C 

d 

sl 

= 

3 

4 

C 

f 

d 

α 

24 

= 

α Re 

p 

p 

α 

f 

ρ 

f 

d 

p 

u 

f 

− 

( α Re ) 

−2.65 

f 

( 1 0.15 

) 

0.687 

+ 

f 

u 

p 

α 

p 

, 

, 

α f 

≤ 0.8: 

K 

sl 

α 

s 

= 150 

α 

f 

2 

μ 

d 

f 

2 

p 

α 

sρ 

f 

+ 1.75 

u 

f 

− 

d 

p 

u 

p 

. 

www.cfdem.com 



14

An Open-Source CFD – DEM Perspective 

„LammpsFoam“ 

init 

particle data 

OpenFoam 

Solver 

LIGGGHTS 

end 

flow data 


15


Implementation 

start 

DEM solver calculates 

100 time-steps, 

and transfers particle 

data to CFD solver 

CFD solver calculates 

1 time-step 

CFD solver fetches 

DEM particle data 

CFD solver searches 

cell each particle is in 

CFD solver calculates 

volume fraction and 

momentum coupling 

CFD solver transfers 

drag forces to DEM 


16


Implementation 

“Chimera” approach for momentum exchange 

mesh for 

exchange fields 

K sl , α 

mesh for CFD 

calculations 

DEM domain 


17


Validation example 

Pressure drop and onset of fluidization in a cylindrical granular bed: 

u f 0 – 0.02 m/s 

g 9.81 m/s 2 

μ f 1.5 e-4 m 2 /s 

ρ s 200 kg/m 3 

d s 0.001 m (10000 particles) 

Fluid boundary conditions 

Inital particle packing 


18



validation case, onset of fluidization 

inlet velocity 

void fraction 


19



pressure drop 

according to analytics, the 

minimum fluidization velocity is 

at 0.012 m/s 


20



Performance: 

excessive performance tests have not yet been carried out, a first hint: 

10000 particles 

1h for 1s simulation time 

on 2 2.4 GHz processors 


21



Partly fluidized bed (inhomogeneous velocity BC): 

Fluid boundary conditions 

Inital particle packing 


22



Partly fluidized bed (inhomogeneous velocity BC): 


23

An Open Source CFD-DEM Perspective

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