Granular Matter

, 20:39 | Cite as

Mixtures of hard and soft grains: micromechanical behavior at large strains

Original Paper
  • 14 Downloads

Abstract

In this paper, several simulations involving the compaction and the shearing of mixtures of hard and soft grains are performed in 2D plane-strain conditions. The multibody meshfree numerical tool developed for this purpose is first presented, and the focus is then put on the influence of the proportions of rigid and deformable grains in the mixture on the mechanical response at large strains. Dedicated postprocessing techniques reveal a wide range of behaviors, both in terms of macroscopic response and in micromechanical phenomena. Broadly speaking, the strength and the dilatancy of the mixture decrease when the proportion of soft grains is increased. There are, however, interesting exceptions to this trend at very high and very low contents of soft grains, which are analyzed in dedicated sections. This preliminary work paves the way to more comprehensive studies of this class of materials, which is still hardly understood but presents some potential in a wide range of applications.

Keywords

Granular materials Soft and hard mixtures Deformable grains Meshfree methods Discrete Element Modeling Large strain behavior 

Notes

Acknowledgements

Valuable and useful comments by the two anonymous reviewers are gratefully acknowledged by the author.

Compliance with ethical standards

Conflict of interest

The author acknowledges that this study contains original material, as a result of a purely academic study without any kind of private funding or conflict of interest. Its publication has been approved tacitly by the responsible authorities at the institute where the work has been carried out.

Supplementary material

10035_2018_812_MOESM1_ESM.avi (40.2 mb)
Video 1: Kinematics of the simulations (video 41,146 KB)
10035_2018_812_MOESM2_ESM.avi (85.6 mb)
Video 2: von Mises stress fields of the simulations (video 87,662 KB)

Video 3: Strain rate fields of the simulations (video 1,40,893 KB)

References

  1. 1.
    Cundall, P.A., Strack, O.D.L.: A discrete numerical model for granular assemblies. Géotechnique 29(1), 47–65 (1979)CrossRefGoogle Scholar
  2. 2.
    Mirea, D.A., Trunfio-Sfarghiu, A.-M., Matei, C.I., Munteanu, B., Piednoir, A., Rieu, J.P., Blanchin, M.G., Berthier, Y.: Role of the biomolecular interactions in the structure and tribological properties of synovial fluid. Tribol. Int. 59, 302–311 (2013)CrossRefGoogle Scholar
  3. 3.
    McClements, D.J., Guzey, D.: Formation, stability and properties of multilayer emulsions for application in the food industry. Adv. Colloid. Interface Sci. 128–130, 227–248 (2006)Google Scholar
  4. 4.
    Wang, J.D., Zhu, Y.F., Zhou, X.W., Sui, G., Liang, J.: Preparation and mechanical properties of natural rubber powder modified by carbon nanotubes. J. Appl. Polym. Sci. 100, 4697–4702 (2006)CrossRefGoogle Scholar
  5. 5.
    Wornyoh, E.Y.A., Jasti, V.K., Higgs, C.F.: A review of dry particulate lubrication: powder and granular materials. J. Tribol. 192(2), 438–449 (2007)CrossRefGoogle Scholar
  6. 6.
    Mollon, G.: A numerical framework for discrete modelling of friction and wear using Voronoi polyhedrons. Tribol. Int. 90, 343–355 (2015)CrossRefGoogle Scholar
  7. 7.
    Galen, S., Zavaliangos, A.: Strength anisotropy in cold compacted ductile and brittle powders. Acta Mater. 53, 4801–4815 (2005)CrossRefGoogle Scholar
  8. 8.
    Razavi Hesabi, Z., Hafizpour, H.R., Simchi, A.: An investigation on the compressibility of aluminum/nano-alumina composite powder prepared by blending and mechanical millig. Mater. Sci. Eng. A 454–455, 89–98 (2007)CrossRefGoogle Scholar
  9. 9.
    Kruth, J.-P., Levy, G., Klocke, F., Childs, T.H.C.: Consolidation phenomena in laser and powder-bed based layered manufacturing. Ann. CIRP 56(2), 730–759 (2007)CrossRefGoogle Scholar
  10. 10.
    Costa, S., Höhler, R., Cohen-Addad, S.: The coupling between foam viscoelasticity and interfacial rheology. Soft Matter 9, 1100–1112 (2013)ADSCrossRefGoogle Scholar
  11. 11.
    Lee, J.-S., Dodds, J., Santamarina, J.C.: Behavior of rigid-soft particle mixtures. J. Mater. Civ. Eng. 19(2), 179–184 (2007)CrossRefGoogle Scholar
  12. 12.
    Zhang, S.L., Xin, Z.X., Zhang, Z.X., Kim, J.K.: Characterization of the properties of thermoplastic elastomers containing waste rubber tire powder. Waste Manage. (Oxford) 29, 1480–1485 (2009)CrossRefGoogle Scholar
  13. 13.
    Harthong, B., Jerier, J.-F., Richefeu, V., Chareyre, B., Doremus, P., Imbault, D., Donzé, F.-V.: Contact impingement in packings of elastic–plastic spheres, application to powder compaction. Int. J. Mech. Sci. 61, 32–43 (2012)CrossRefGoogle Scholar
  14. 14.
    Gustafsson, G., Haggblad, H.-A., Jonsen, P.: Multi-particle finite element modelling of the compression of iron pellets with statistically distributed geometric and material data. Powder Technol. 239, 231–238 (2013)CrossRefGoogle Scholar
  15. 15.
    Gethin, D.T., Ransing, R.S., Lewis, R.W., Dutko, M., Crook, A.J.L.: Numerical comparison of a deformable discrete element model and an equivalent continuum analysis for the compaction of ductile porous material. Comput. Struct. 79, 1287–1294 (2001)CrossRefGoogle Scholar
  16. 16.
    Gethin, D.T., Lewis, R.W., Ransing, R.S.: A discrete deformable element approach for the compaction of powder systems. Model. Simul. Mater. Sci. Eng. 11, 101–114 (2003)ADSCrossRefGoogle Scholar
  17. 17.
    Jean, M.: The non-smooth contact dynamics method. Comput. Methods Appl. Mech. Eng. 177(3–4), 235–257 (1999)ADSMathSciNetCrossRefMATHGoogle Scholar
  18. 18.
    Onate, E., Idelsohn, S.R., Del Pin, F., Aubry, R.: The particle finite element method—an overview. Int. J. Comput. Methods 1(2), 267–307 (2004)CrossRefMATHGoogle Scholar
  19. 19.
    Cante, J., Devalos, C., Hernandez, J.A., Oliver, J., Jonsén, P., Gufstafsson, G., Häggblad, H.-A.: PFEM-based modeling of industrial granular flows. Comput. Part. Mech. 1(1), 47–70 (2014)CrossRefGoogle Scholar
  20. 20.
    Nezamabadi, S., Nguyen, T.H., Delenne, J.-Y., Averseng, J., Frank, X., Radjai, F.: MPM with frictional contacts for application to soft particulate materials. Procedia Eng. 175, 141–147 (2017)CrossRefGoogle Scholar
  21. 21.
    Dupin, M.M., Halliday, I., Care, C.M., Alboul, L., Munn, L.L.: Modeling the flow of dense suspensions of deformable particles in three dimensions. Phys. Rev. E 75, 066707 (2007)ADSCrossRefGoogle Scholar
  22. 22.
    MacMeccan, R.M., Clausen, J.R., Neitzel, G.P., Aidun, C.K.: Simulating deformable particle suspensions using a coupled lattice-Boltzmann and finite-element method. J. Fluid Mech. 618, 13–39 (2008)ADSMathSciNetCrossRefMATHGoogle Scholar
  23. 23.
    Wu, J., Aidun, C.K.: Simulating 3D deformable particle suspensions using lattice Boltzmann method with discrete external boundary force. Int. J. Numer. Methods Fluids 62, 765–783 (2010)MATHGoogle Scholar
  24. 24.
    Duvernois, V., Marsden, A.L., Shadden, S.C.: Lagrangian analysis of hemodynamics data from FSI simulation. Int. J. Numer. Methods Biomed. Eng. 29, 445–461 (2013)MathSciNetCrossRefGoogle Scholar
  25. 25.
    Liao, C.-T., Wu, Y.-F., Chien, W., Huang, J.-R., Chen, Y.-L.: Modeling shear-induced particle ordering and deformation in a dense soft particle suspension. J. Phys. Condens. Matter 29, 435101 (2017)CrossRefGoogle Scholar
  26. 26.
    Mollon, G.: A multibody meshfree strategy for the simulation of highly deformable granular materials. Int. J. Numer. Methods Eng. 108(12), 1477–1497 (2016)MathSciNetCrossRefGoogle Scholar
  27. 27.
    Mollon, G.: A unified numerical framework for rigid and compliant granular materials. Comput. Part. Mech. (2018).  https://doi.org/10.1007/s40571-018-0187-6 Google Scholar
  28. 28.
    Nayroles, B., Touzot, G., Villon, P.: Generalizing the finite element method: diffuse approximation and diffuse elements. Comput. Mech. 10, 307–318 (1992)CrossRefMATHGoogle Scholar
  29. 29.
    Belytschko, T., Lu, Y.Y., Gu, L.: Element-free Galerkin methods. Int. J. Numer. Methods Eng. 37, 229–256 (1994)MathSciNetCrossRefMATHGoogle Scholar
  30. 30.
    MiDi, G.D.R.: On dense granular flows. Eur. Phys. J. E 14, 341–365 (2004)CrossRefGoogle Scholar
  31. 31.
    Mollon, G., Zhao, J.: Fourier–Voronoi-based generation of realistic samples for discrete modelling of granular materials. Granul. Matter 14, 621–638 (2012)CrossRefGoogle Scholar
  32. 32.
    Mollon, G., Zhao, J.: Generating realistic 3D sand particles using Fourier descriptors. Granul. Matter 15(1), 95–108 (2013)CrossRefGoogle Scholar
  33. 33.
    Mollon, G., Zhao, J.: 3D generation of realistic granular samples based on random fields theory and Fourier shape descriptors. Comput. Methods Appl. Mech. Eng. 279, 46–65 (2014)ADSCrossRefGoogle Scholar
  34. 34.
    Mollon, G., Zhao, J.: Characterization of fluctuations in granular hopper flow. Granul. Matter 15(6), 827–840 (2013)CrossRefGoogle Scholar
  35. 35.
    Mollon, G., Richefeu, V., Villard, P., Daudon, D.: Discrete modelling of rock avalanches: sensitivity to block and slope geometries. Granul. Matter 17(5), 645–666 (2015)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.LaMCoS, INSA-Lyon, CNRS UMR5259Université de LyonVilleurbanneFrance

Personalised recommendations