Simulation of granular matter Martin Servin Department of Physics / UMIT Research Lab.

En presentation över ämnet: "Simulation of granular matter Martin Servin Department of Physics / UMIT Research Lab."— Presentationens avskrift:

1 Simulation of granular matter Martin Servin Department of Physics / UMIT Research Lab

2 Agenda i Malmberget 20-21 april Tisdag 20/1 –besök i kulrullningsverket –frågor och diskussion med Kjell-Ove –arbete i FoU-huset Onsdag 21/1 –möte Martin och Kent kring doktorandprojektet (kontrakt, kommunikation, urval kandidater mm) [1 timme] –möte alla [1-2 timme] status & plan för PellIT-projektet (ProcessIT) idéer kring rullkretssimulator, modell, beräkning validering och utdata målsättning under 2010 –arbete i FoU-huset

3 Status och plan PellIT 2009 - förstudie resurs: 9 manmån, M Servin, C Lacoursière, K Bodin, ProcessIT resultat: PhD förslag, Volvo CE + Algoryx, balling plant simulator, nya metoder och modeller, modsim granular network Tekniska utmaning:  geometrier (trimesh, distance fields)  adaptiv upplösning ( -> merge/split) ☐ integrera constraint fluid i AgX ☐ GPGPU och PCG-lösare i AgX-> AgX 2.0 ☐ viskoplasticitetsmodell

4 Status och plan PellIT 2009 - förstudie Nya resultat merge/split: 2-200 times speedup hybrid direct-iterative solver through new LCP splitting method

5 Status och plan PellIT 2009 - förstudie Nya resultat merge/split: 2-20 times speedup hybrid direct-iterative solver through new LCP splitting method

6 Status och plan PellIT 2010 - FoU-projekt resurs 9 manmån + 75% projektassistent, ProcessIT övrig resurs doktorand, LKAB + UmU företagsforskarskola projektass, examensarbete 6 manmån, UMU X manmån, Algoryx/Oryx/Volvo CE Personal – UMIT Protolab –Forskare: Kenneth Bodin, Claude Lacoursière, Kenneth Bodin –Projektass: Mona Forsman, Stefan Hedman –Examensarbete: John Nordberg, Olof Sabelström, Adam Serhnheim, Kalle Sjöström? –doktorand:… –AgX: Anders Backman, Niklas Melin, Nils Hjelte, Martin Nilsson,…

7 Status och plan PellIT 2010 - FoU-projekt målsättning 2010 –preliminära flödesstudier i simulator – flödesmönster i delsystem –re-design av utlägg? analys rullsikt? sluten process? –kritisk analys av pseudo-partikel-modell –anpassad viskoplasticitetsmodell (SPH, rigid DEM) –integrera constraint-SPH i simulator – 100K partiklar, 10 Hz –numeriska metoder för att accelerera simulering (PCG, multicore, GPGPU, splitting, merge/split, kontaktreducering) –produkt?

8 Status och plan PellIT 2010 - FoU-projekt Aktiviteter –systematiska studier av flöden (Mona F, Martin S) –kritisk analys av pseudo-partikel-modell (Mona F, Martin S) –re-design av utlägg? analys rullsikt? sluten process? –simulator experiment-pipeline (Mona F, Stefan H) –materialparametrisering & validering (Martin S, Mona F + LTU) –utveckling nya modeller och beräkningstekniker anpassad viskoplasticitetsmodell (Martin S, Kenneth B, John N + LTU) merge/split (Martin S) PCG-lösare för multicore och GPGPU (Kenneth B, Claude L, Adam S, Stefan H) parallelization of sparse-block computations (Claude L, Olof Sabelström) kontaktreducering (Claude L) –implementation av nya metoder i AgX (Algoryx) –integrera constraint-SPH i simulator – 100K partiklar, 10 Hz (Algoryx) –produktplan?

9 Ideas on balling plant simulator, models, numerical computations Balling plant simulator User philosophy: fixed - flexible - full user control Sub-systems: balling drum, feeder, input transporters, exit transporter, roller screen, other transporters Functionality: visualization, instantaneous data report, processed data report, optimization tools, load & save Models Rigid body-based DEM Constraint based SPH Merge/split, viscoplastic flow Adaptive hybrid model Computational techniques Direct Iterative Hybrid GPGPU/OpenCL

10 Ideas on balling plant simulator, models, numerical computations Adaptive DEM-SPH hybrid models for particulate flow P

11 Ideas on balling plant simulator, models, numerical computations Adapt Jop’s viscoplastic model (Nature 2006) to constraint based model -> produce constraint based interaction model for SPH or H/P-particle model

12 Ideas on balling plant simulator, models, numerical computations

13 Balling plant – measuring zones Particle data –kinematics –dynamics Measuring zone –2D layer with thickness d Post-processing in Matlab –sampling of fields: density, velocity, pressure, shear –particle statistics –sample trajectories Data and visualization –automatic report generation –data plots –Matlab / VTK / Asymptote

14 Balling plant – measuring zones

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18 Questions Product? Purpose and use of software? UmU research for developing methods and models Algoryx – code library sold to customers realizing various simulators Joint research for studying flow behavior and the balling process LKAB or 3 rd party research for re-designing balling process and equipment LKAB for internal education around balling process 3 rd party for R&D -> demands on flexibility, usability and visualization techniques -> fix simulator vs coupling to CAD/CAE vs interactive 3D tool (Algodoo 3D) -> who wants to own and maintain software tool? Primary sub-system for 2010 balling drum flow – recreate, analyze, “control” ? feeder – recreate, analyze, “re-design”? Roller screen? – imperfect flow, pellet quality, “re-design”?

19 Questions Questions to simulator 2010 Quasiparticles – how much does size varies? Quasiparticles – error vs timestep? Quasiparticles – parametrization of particle interactions? Rheology and trajectories – dependency on rotation speed and material parameters Material parameters & model validation single green pellet: restitution, friction, rolling friction, adhesion, viscoelasticity, plasticity, adhesion – Agglolab? slurry: friction angle, yeild function, compaction ratio pellets slab: friction angle, yeild function – construct Jop’s setup? UmU – LKAB collaboration continuously involved in analysis? – data exchange server, video meetings 6-12 months reports