SLIDE 1 Di Discre crete e Element ement Met ethods
n STAR-CC
Petr etr Kodl CD CD-ada dapc pco
SLIDE 2 Engin ginee eerin ing num umeric erical l met ethod
late mot
ge numb mber r of interact eracting ing discret ete e object cts Co Comparabl mparable e to short ran ange e force MD simulati lation
ethodo dology
Established by P.A. Cundall, O.D.L. Strack: A discrete numerical model for granular assemblies. Geotechnique, 29:47–65, 1979 Classical mechanical method Mesh free CPU intensive
– Transient – Explicit schemes
Provides detail resolution other methods can not achieve Used to describe wider class of methods but in terms of STAR-CCM+ we focus on granular flows Bulk k state e results lts from partic ticle e intera ract ction
nsti titutiv tutive e relat ation ion is used
Introdu
ction to Disc scre rete e Elemen ement t Met ethods
EM)
SLIDE 3
Anisotropy
– Stress chains – Large spatio-temporal fluctuations
Persistent contacts Shear resistance Jamming ming and arching ng Reynolds’ dilatancy
Granular nular materials erials and their eir specif ific ic proper ertie ties s
SLIDE 4
Sand Food particles Metal particles Capsules and pills Slurries Grains Soil
Granular nular materials erials
SLIDE 5
When does it make sense?
– Highly loaded particulate flows – Collisions are important – Particle shape is important – Details of collisions are important – Typical granular flow properties are studied – jamming, shearing
What are the limits for practical problems?
– Fine grain particles (<1e-4) – Achievable but the CPU time can be prohibitively expensive for industrial problems – The collision details are typically not critical outcome – Very large particles (>1m) where the local deformation is important and the contact law small deformation assumption is not valid
DEM applicat ications ions
SLIDE 6 Impl mpleme ement nted d with thin in Lagra rangia ngian frame mewor
– Reuses known concepts
- Lagrangian phase
- Injectors
- Boundary interactions
- Sub stepping of the solution
Ex Extend ends s conc ncep ept t of Materi rial al particle cle Additi tion
l tracki cking ng of
– Orientation – Angular motion – Inter-particle collisions
Soft t particle ticle model
nalty fun uncti tion
sed force ce evaluat uation) ion) Not
istical – 1 parcel l = 1 partic icle le
DEM in STAR-CC CCM+
SLIDE 7 5.06 - 28 Oct, 2010
– Initial DEM release – Hertz Mindlin contact model – Spherical and composite particles – Moving walls via applied velocity condition – Stationary mesh and MRF
6.02 - 28 Feb, 2011
– Rigid mesh motion – Phase specific boundary behavior – Drag laws suitable for highly loaded flows
- Ergun equation – Gidaspow
Timeline meline of DEM in STAR-CC CCM+
SLIDE 8 6.04 - 1 July 2011
– Walton-Braun linear hysteretic contact model – Parallel bonds – Flexible / breakable particle clumps – Lattice injectors – Charged particles
6.06 – October 2011
– Cohesive particles – Improved particle tracking code – User controlled time steps – Additional drag coefficients
– Two way coupling for charged particles
Timeline meline of DEM in STAR-CC CCM+
SLIDE 9
7.02
– Randomized position injectors – Porosity injection limits – Improved particle-flow interaction through fast estimate of projected area and length – Contact data sources, reports and visualization
7.04
– Particle trapping walls – Improved randomization of initial particle distribution – Performance optimizations both in serial and parallel
Timeline meline of DEM in STAR-CC CCM+
SLIDE 10
– Comparison of contact force models for the simulation of collisions in DEM based granular flow codes, Alberto Di Renzo, Francesco Paolo Di Maio, 2004, Chemical Engineering Science – Aluminum oxide spheres shot against glass plate with varying impact angle – Apparent coefficient or tangential restitution, rotation rate and rebound angle compared to laboratory experiment and reference implementation
Valid idation ation –conta tact t mecha hanics nics
SLIDE 11
– Discrete Particle Simulation of Solid Flow in Model Blast Furface, Zongyan Zhou, Haiping Zhu ISIJ Vol 45, 2005 – Studies solid flow patter in blast furnace – STAR-CCM+ compared to experiment and reference results
Valid idation ation – granular ular flow patt ttern ern format mation ion
SLIDE 12
– STAR-CCM+ solution compared to Ergun equation – Tested case – porous bed with periodic walls – Analytic solution pressure drop ~ 108Pa
Valid idation ation – pressure ssure drop
SLIDE 13
DEM EM Solution ions s ED EDEM EM
– Mature industry focused code – STAR-CCM+ will be compared to most frequently in terms of DEM physic/features – Founded 2002 – First release of the code in 2005 – First industrial grade release - 1.2 – May 2007 – Second generation solver and internal architecture code released as version 2.0 - 9 May 2008 – Current release EDEM 2.4 - September 16, 2011
Compe petitiv titive e analysis ysis
SLIDE 14 STAR AR-CC CCM+ M+
– Distributed memory (MPI)
- Domain decomposition
- Cluster friendly
– 2d, 3d – Volumetric representation
- + Allows to solve coupled problems
- - Extra work required for meshing
– Rich, multi physics framework
ED EDEM EM
– Shared memory (OpenMP)
- Loop parallelism
- Single workstation
– 3d – Surface representation
- + Almost no surface preparation
- - Makes coupling difficult
– Single purpose solver code
Compe petitiv titive e analysis ysis – basic ic charact acteristics eristics
SLIDE 15
STAR-CCM+ EDEM
Spherical particles x x Rigid composites x x Breakable flexible clumps x Custom coding Hertz Mindlin x x Hysteretic model x x Parallel bonds x x Cohesion x x Linear spring Can use hysteretic model x JKR Can use cohesion model x Electrostatics 2 way coupled Limited Particle/flow interaction 2 way coupled No longer supported
Compe petitiv titive e analysis ysis
SLIDE 16
STAR-CCM+ EDEM
Heat transfer particle-particle, particle-flow, particle-particle radiation Particle-particle Interfaces General Parallel planes Particle shape editor x x Moving geometry Rigid body motion Rigid body motion Easy to setup – no meshing required Transient post processing Track files Full solution replay
Compe petitiv titive e analysis ysis
SLIDE 17 Conc nclusi sion
– Competitive in terms of implemented features – Advantage for complex physics
- Reuse of feature implemented for general Lagrangian framework
- Ability to implement more complex physics due to the background FV discretization
– Further improvements
- Simplify the workflow for complex moving geometries
- Transient post processing and solution history
Compe petitiv titive e analysis ysis
SLIDE 18 Not
y to qua uantify fy – depen pends ds on chara ract cteris istics tics of particula icular r case
– Packing structure – Distribution of particles in the computational domain – Amount of physics – Coupling – Overall case size
- Overhead of the STAR-CCM+ framework – mostly affecting small cases
- Large cases become memory bound when running on single machine mostly due to
irregular memory access patterns
Performanc
e and scalability ability
SLIDE 19 CPU time e vs vs num umber ber of partic icles les
– Naively O(N^2) – Ideally O(N)
- Good collision detector should linearize the
detection time
– Example
- CPU time / solver step vs # of particles
- # of particles up to 150000
- Densely packed
- Credit: Phillip Morris Jones, London Office
Performanc
e and scalability ability
SLIDE 20 Solver er time me vs vs # of CP
– 3d Hopper – 100 000 spherical particles – Well distributed – Credit: Lucia Sclafani
Performanc
e and scalability ability
SLIDE 21 Physics sics
– Liquid bridges, capillary forces, free surface-particle interaction in VOF – Mass transfer, drying, coating – Smooth simulation physics decomposition DEM, FEA, EMP – Surface only DEM
Perform
nce and scalabil bilit ity
– Improved cache coherency for single workstation runs – Dynamic particle centric load balancing
GUI and d us usabili ility ty
– Transient post processing and solution snapshots – CAD import and interpolation of particle shape by sphere trees
Future ure development
SLIDE 22
Exam amples ples
SLIDE 23
Thank nk you Que uest stions? ions?
