Abstract
There are computation time constraints caused by the number and size of particles in the powder packing simulation using DEM. In this paper, newly suggested packing model transforms a general packing sequence —particle generation, stack, and compression-into particle generation and packing by growing particles. To verify the new packing model, it was compared using three contact models widely used in DEM, in terms of radial distribution function, porosity, and coordination number. As a result, contact between particles showed a similar trend, and the pore distribution was also similar. Using the new packing model can reduce simulation time by 400 % compared to the normal packing model without any other coarse graining methods. This model has only been applied to particle packing simulations in this paper, but it can be expanded to other simulations with complex domain based on DEM.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Abbreviations
- F n :
-
Normal force acting perpendicular to the particle
- F t :
-
Tangential force acting to the particle
- k n :
-
Spring stiffness coefficient in the normal direction
- k s :
-
Spring stiffness coefficient in the tangential direction
- δ n :
-
Overlap between particles in the normal direction
- δ t :
-
Overlap between particles in the tangential direction
- ν n :
-
Damping coefficient in the normal direction
- v t :
-
Damping coefficient in the tangential direction
- ∆V contact :
-
Relative velocity between
- μ :
-
Coefficient of friction
- r p :
-
Radius of particle
- r * :
-
Equivalent radius
- E :
-
Young’s modulus
- E * :
-
Equivalent Young’s modulus
- G * :
-
Shear modulus
- G :
-
Equivalent shear modulus
- v :
-
Poisson’s ratio
- m * :
-
Equivalent mass
- e p :
-
Repulsive coefficient of the particle
- a :
-
Contact radius of the particle
- y :
-
Surface energy of the particle
- ρ :
-
Density of the particle
- ε p :
-
Coefficient of restitution
- μ p :
-
Friction coefficient for particle to particle
- μ w :
-
Friction coefficient for particle to wall
- Φ :
-
Porosity
- V V :
-
Volume of the pore
- V T :
-
Entire volume
References
X. Fu, M. Dutt, A. C. Bentham, B. C. Hancock, R. E. Cameron and J. A. Elliott, Investigation of particle packing in model pharmaceutical powders using X-ray microtomography and discrete element method, Powder Technol., 167 (2006) 134–140.
W. Nan, M. Pasha, T. Bonakdar, A. Lopez, U. Zafar, S. Nadimi and M. Ghadiri, Jamming during particle spreding in additive manufacturing, Powder Technol., 338 (2018) 253–262.
W. X. Xu and H. S. Chen, Numerical investigation of effect of particle shape and particle size distribution on fresh cement paste microstructure via random sequential packing of do-decahedral cement particles, Comput. Struct., 114 (2013) 35–45.
S. G. Lee and D. H. Jeon, Effect of electrode compression on the wettability of lithium-ion batteries, J. Power Sources (2014) 363–369.
A. B. Yu and N. Standish, Porosity calculation of multi-component mixtures of spherical particles, Powder Technol., 52 (1987) 233–241.
A. B. Yu and N. Standisth, A study of the packing of particles with a mixture size distribution, Powder Technol., 76 (1993) 113–124.
G. T. Nolan and P. E. Kavanagh, Computer simulation of random packing of hard sphere, Powder Technol., 72 (1992) 149–155.
A. Bertei, C.-C. Chueh, J. G. Pharoah and C. Nicolella, Modified collective rearrangement sphere-assembly algorithm for random packings of nonspherical particles: towards engineering applications, Powder Technol., 253 (2014) 311–324.
Y. Muguruma, T. Tanaka and Y. Tsuji, Numerical simulation of particulate flow with liquid bridge between particles (simulation of centrifugal tumbling granulator), Powder Technol., 109 (2000) 49–57.
K. Washino, H. S. Tan, M. J. Hounslow and A. D. Salman, A new capillary force model implemented in micro-scale CFD-DEM coupling for wet granulation, Chem. Eng. Sci., 93 (2013) 197–205.
P. A. Cundall and O. D. L. Strack, A discrete numerical model for granular assemblies, Geotechnique, 29 (1979) 47–65.
S. Lee and J. Park, Standardized friction experiment for parameter determination of discrete element method and its validation using angle of repose and hopper discharge, Multiscale Sci. Eng., 1 (2019) 247–255.
Y. He, T. J. Evans, A. B. Yu and R. Y. Yang, Numerical modelling of die and unconfined compactions of wet particles, Procedia Eng., 102 (2015) 1390–1398.
H. Tangri, Y. Guo and J. S. Curtis, Packing of cylindrical particles: DEM simulations and experimental measurements, Powder Technol., 317 (2017) 72–82.
X. L. Deng and R. N. Dave, Dynamic simulation of particle packing influenced by size, aspect ratio and surface energy, Granular Matter, 15 (2013) 401–415.
E. J. R. Parteli, J. Schmidt, C. Blumel, K.-E. Wirth, W. Peukert and T. Poschel, Attractive particle interaction forces and packing density of fine glass powders, Sci. Rep., 4 (2014) 6227.
Y. S. Lee, P. Nandwana and W. Zhang, Dynamic simulation of powder packing structure for powder bed additive manufacturing, Int. J. Adv. Manuf. Technol., 96 (2018) 1507–1520.
M. Kremmer and J. F. Favier, A method for representing boundaries in discrete element modelling-part 2: kinematics, Int. J. Numer. Meth. Eng., 51 (2001) 1423–1436.
J. Viacek and M. Molenda, Effect of particles size distribution on micro- and macromechanical response of granular packings under compression, Int. J. Solids Struct., 51 (2014) 4189–4195.
J. Hearvig, U. Kleinhans, C. Wieland, H. Spliethoff, A. L. Jensen, K. Sorensen and T. J. Condra, On the adhesive JKR contact and rolling models for reduced particle stiffness discrete element simulations, Powder Technol., 319 (2017) 472–482.
H. Mio, A. Shimosaka, Y. Shirakawa and J. Hidaka, Optimum cell size for contact detection in the algorithm of the discrete element method, J. Chem. Eng. Japan, 38(12) (2005) 969–975.
M. Sakai and S. Koshizuka, Large-scale discrete element modeling in pneumatic conveying, Chem. Eng. Sci., 64 (2009) 533–539.
M. Sakai, Y. Yamada, Y. Shigeto, K. Shibata, V. M. Kawasaki and S. Koshizuka, Large-scale discrete element modeling in a fluidized bed, Int. J. Numer. Meth. Fluids., 64 (2010) 1319–1335.
R. Y. Yang, R. P. Zou and A. B. Yu, Computer simulation of the packing of fine particles, Phys. Rev. E, 63 (2000) 3900.
K. J. Dong, R. P Zou, R. Y. Yang, A. B. Yu and G. Roach, DEM simulation of cake formation in sedimentation and filtration, Minerals Eng., 22 (2009) 921–930.
E. M. B. Campello and K. R. Cassares, Rapid generation of particle packs at high packing ratios for DEM simulation of granular compacts, Latin Am. J. Solids Struct., 13(1) (2016) 25–50.
J. F. Jerier, V. Richefeu, D. Imbault and F. V. Donzé, Packing spherical discrete elements for large scale simulations, Comput. Meth. Appl. Mech. Eng., 199 (2010) 1668–1676.
R. D. Mindlin, Compliance of elastic bodies in contact, J. Appl. Mech., 16 (1949) 259–268.
K. L. Johnson, K. Kendall and A. D. Roberts, Surface energy and the contact of elastic solids, Math. Phys. Sci., 324 (1971) 301–313.
W. S. Jodrey and E. M. Tory, Computer simulation of close random packing of equal spheres, Phys. Rev. A, 32(4) (1985) 2347.
T. Jia, Y. Zhang and J. K. Chen, Simulation of granular packing of particles with different size distributions, Comput. Mater. Sci., 51 (2012) 172–180.
J. Nam, J. Lyu and J. Park, Packing structure analysis of flexible rod particles in terms of aspect ratio, bending stiffness, and surface energy, Powder Technol., 357 (2019) 232–239.
Acknowledgments
This work was supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology [NRF-2018R1A2B 2004207] and the MSIT (Ministry of Science and ICT), Korea, under the Grand Information Technology Research Center support program (IITP-2020-2020-0-01612) supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation).
Author information
Authors and Affiliations
Corresponding author
Additional information
Jinsu Nam is a Ph.D. candidate at the Department of Mechanical Design Engineering, Kumoh National Institute of Technology, Gumi, Korea. His research interests include particle packing simulation and CFD-DEM coupling simulation.
Jaehee Lyu is a Ph.D. candidate at the Department of Mechanical Design Engineering, Kumoh National Institute of Technology, Gumi, Korea. Her research interests are Discrete Element Method and powder packing.
Junyoung Park is a Professor at the Department of Mechanical Design Engineering, Kumoh National Institute of Technology, Gumi, Korea. He received his Ph.D. in Mechanical Engineering from Purdue University, IN, USA.
His research interests include particle technology and pedestrian flow analysis.
Rights and permissions
About this article
Cite this article
Nam, J., Lyu, J. & Park, J. Particle generation to minimize the computing time of the discrete element method for particle packing simulation. J Mech Sci Technol 36, 3561–3571 (2022). https://doi.org/10.1007/s12206-022-0632-6
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12206-022-0632-6