Di Discre crete e Element ement Met ethods ods in n STAR-CC -CCM+ Petr etr Kodl CD CD-ada dapc pco
Introdu oduction ction to Disc scre rete e Elemen ement t Met ethods ods (DEM) EM) Engin ginee eerin ing num umeric erical l met ethod ods used to simulat late mot otion on or large ge numb mber r of interact eracting ing discret ete e object cts Comparabl Co mparable e to short ran ange e force MD simulati lation ons in met ethodo dology ogy 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 ons – no cons nsti titutiv tutive e relat ation ion is used
Granular nular materials erials and their eir specif ific ic proper ertie ties s Anisotropy – Stress chains – Large spatio-temporal fluctuations Persistent contacts Shear resistance Jamming ming and arching ng Reynolds’ dilatancy
Granular nular materials erials Sand Food particles Metal particles Capsules and pills Slurries Grains Soil
DEM applicat ications ions 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 in STAR-CC CCM+ Impl mpleme ement nted d with thin in Lagra rangia ngian frame mewor ork – Reuses known concepts • Lagrangian phase • Injectors • Boundary interactions • Sub stepping of the solution Extend Ex ends s conc ncep ept t of Materi rial al particle cle Additi tion onal l tracki cking ng of – Orientation – Angular motion – Inter-particle collisions Soft t particle ticle model odel (penalty nalty fun uncti tion on based sed force ce evaluat uation) ion) Not ot statistical istical – 1 parcel l = 1 partic icle le
Timeline meline of DEM in STAR-CC CCM+ 5.06 - 28 Oct, 2010 6.02 - 28 Feb, 2011 – Initial DEM release – Rigid mesh motion – Hertz Mindlin contact model – Phase specific boundary behavior – Spherical and composite particles – Drag laws suitable for highly loaded flows – Moving walls via applied velocity • Ergun equation – Gidaspow condition – Stationary mesh and MRF
Timeline meline of DEM in STAR-CC CCM+ 6.04 - 1 July 2011 6.06 – October 2011 – Walton-Braun linear hysteretic – Cohesive particles contact model – Improved particle tracking code – Parallel bonds – User controlled time steps – Flexible / breakable particle – Additional drag coefficients clumps • Haider Levenspiel – Lattice injectors – Two way coupling for charged – Charged particles particles
Timeline meline of DEM in STAR-CC CCM+ 7.02 7.04 – Randomized position injectors – Particle trapping walls – Porosity injection limits – Improved randomization of initial particle distribution – Improved particle-flow interaction through fast estimate of projected – Performance optimizations both in area and length serial and parallel – Contact data sources, reports and visualization
Valid idation ation – conta tact t mecha hanics nics – 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 – granular ular flow patt ttern ern format mation ion – 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 – pressure ssure drop – STAR-CCM+ solution compared to Ergun equation – Tested case – porous bed with periodic walls – Analytic solution pressure drop ~ 108Pa
Compe petitiv titive e analysis ysis 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 – basic ic charact acteristics eristics STAR AR-CC CCM+ M+ ED EDEM EM – Distributed memory (MPI) – Shared memory (OpenMP) • Domain decomposition • Loop parallelism • Cluster friendly • Single workstation – 2d, 3d – 3d – Volumetric representation – Surface representation • + Allows to solve coupled problems • + Almost no surface preparation • - Extra work required for meshing • - Makes coupling difficult – Rich, multi physics framework – Single purpose solver code
Compe petitiv titive e analysis ysis 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 STAR-CCM+ EDEM Heat transfer particle-particle, Particle-particle particle-flow, particle-particle radiation 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 Conc nclusi sion on – 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
Performanc ormance e and scalability ability Not ot easy 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 ormance e and scalability ability 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 ormance e and scalability ability Solver er time me vs vs # of CP – 3d Hopper – 100 000 spherical particles – Well distributed – Credit: Lucia Sclafani
Future ure development opment 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 ormanc 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
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