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DEM simulation of weakly wetted Users committee meeting granular material Short overview of the work done by FG-team imfd DFG-STW, 2014 CONTENT Implementation in Software Capillary bridge models Results of DEM-simulations of

  1. “DEM simulation of weakly wetted Users’ committee meeting granular material” Short overview of the work done by FG-team imfd

  2. DFG-STW, 2014 CONTENT Implementation in Software Capillary bridge models Results of DEM-simulations of split-bottom shear-cell CFD-simulations of the shear cell Conclusions TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 1 imfd

  3. Implementation in Software Pros TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 Old-style code capillary simulations (v2.x) Some problems with Cons High calculation speed MPI-support LIGGGHTS (LAMMPS improved for general granular and granular heat transfer simulations) No MPI-support Lower calculation speed Cons OpenMP-parallelization Reliable, modern code Pros Yade (Yet Another Dynamic Engine) 2 imfd

  4. Capillary bridge models 2. Liquid bridge volume V b TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 schema Capillary bridge Fig. 1: Controlled parameter: Separation particle distance s 3. Rabinovich et al. Input constant parameters: 2. Willett et al. (full and reduced) 1. Weigert et al. Implemented CBMs: 3 imfd θ i 1. Contact angle θ s j V b 3. Surface tension γ

  5. Capillary bridge models 100 TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 Comparison of difgerent kinds of capillary bridge models with experimental Fig. 2: Exp RabL WilF WilR Weig 250 200 150 50 0 350 300 250 200 150 100 50 0 Comparison with experiments of Willett et al. 4 imfd F [ µ N ] a [ µ m ] data from Willett. R p = 2 . 381 mm, V b = 13 . 6 nl, θ = 0 ◦ .

  6. Results of DEM-simulations of split-bottom shear-cell Fig. 3: Setup of split-bottom confjguration DEM parameters TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 5 imfd R p = 2 . 381 mm; ρ = 150 kg / m 3 ; t c = 5 . 4 · 10 − 6 s; e n = e t = 0 . 83 Particle number ≈ 2 · 10 5 ; Rotation period 100s;

  7. Results of DEM-simulations of split-bottom shear-cell Export in text-form, VTK TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 t Snapshots analyze Steady state analyze External libraries: boost, alglib, vtk, eigen3 6 Import of text-data in difgerent formats Written in C++ AVERAGING TECHNIQUES The software to analyze DEM-shear-cell results https://github.com/gladk/rheometeranalyze RheometerAnalyze imfd 1 t +∆ t < φ > = 1 t 2 ∫ φ = φ dt ∫ φ dt t 2 − t 1 ∆ t t 1 t 2 − t 1 >> ∆ t

  8. Results of DEM-simulations of split-bottom shear-cell Typical results from DEM-simulation: Fig. 4: Fig. 5: Fig. 6: Fig. 7: p TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 7 imfd ω τ γ ˙

  9. Results of DEM-simulations of split-bottom shear-cell 30 TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 Fig. 8: p [ Pa ] 80 70 60 50 40 8 20 Local shear stress as a function of local pressure: 10 0 imfd 10 ) ] 8 [ 0 l ) = n ] [ 4 7 l ( n b = 3 V 1 6 x . 0 ( 0 V b . ) 2 ] + [ 3 1 l n 3 4 1 = τ [ Pa ] . x 0 ( 3 V b . 1 + 2 3 1 x . 0 0 τ ( P ) .

  10. Results of DEM-simulations of split-bottom shear-cell RabL, 13nl TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 Fig. 9: RabL, 74nl Dry 1 0.1 100 10 9 imfd η [ Pas ] γ [ s − 1 ] ˙ γ > 0 . 02 s − 1 Apparent shear viscosity η ( ˙ γ ) for ˙

  11. Results of DEM-simulations of split-bottom shear-cell Fig. 10: Fig. 11: Fig. 12: Fig. 13: TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 10 imfd Development of the local shear deformation γ : < γ > ( t = 0 . 0225 s ) < γ > ( t = 2 . 25 s ) < γ > ( t = 4 . 5 s ) < γ > ( t = 9 . 0 s )

  12. Results of DEM-simulations of split-bottom shear-cell t [ s ] TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 both weakly wet and dry state Comparison of shear band position and width as a function of time for Fig. 14: Dry 11 imfd 0 . 26 0 . 24 0 . 22 0 . 2 0 . 18 Rz ± W [ m ] 0 . 16 0 . 14 V b = 13[ nl ] 0 . 12 V b = 74[ nl ] 0 . 1 0 1 2 3 4 5 6 7 8

  13. CFD-simulations of the shear cell Fig. 15: Fig. 16: Fig. 17: Fig. 18: TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 12 imfd U ( t = 0 . 01) s U ( t = 0 . 10) s U ( t = 0 . 30) s U ( t = 1 . 00) s

  14. CFD-simulations of the shear cell R-position [ m ] TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 Normalized velocity profjles from CFD and DEM simulations Fig. 19: DEM z=1.0h DEM z=0.5h DEM z=0.1h CFD z=1.0h CFD z=0.5h CFD z=0.1h 13 imfd 1 . 2 1 0 . 8 0 . 6 ω [ s − 1 ] 0 . 4 0 . 2 0 − 0 . 2 0 50 100 150 200 250 300

  15. Conclusions 1. Implement and compare of difgerent capillary bridge models 2. DEM simulations of the shear cell 3. Micro-macro parameter transitions 4. CFD-simulations of the shear cell (fjrst stage) TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 14 imfd

  16. Conclusions Thank you for your attention! TU Bergakademie Freiberg | IMFD | Gladky | DFG-STW, 2014 | 2014-09-25 15 imfd

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