Journal: Granular Matter

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Abbreviation

Granular Matter

Publisher

Springer

Journal Volumes

ISSN

1434-5021
1434-7636

Description

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Publications 1 - 10 of 51
  • Ngo, Duc; Griffiths, Stephane; Khatri, Devvrath; et al. (2013)
    Granular Matter
  • Peña, A. A.; García-Rojo, R.; Herrmann, Hans Jürgen (2007)
    Granular Matter
  • Plug conveying in a horizontal tube
    Item type: Journal Article
    Strauss, Martin; McNamara, Sean; Herrmann, Hans J. (2007)
    Granular Matter
  • Buarque de Macedo, Robert; Monfared, Siavash; Karapiperis, Konstantinos; et al. (2023)
    Granular Matter
    Engineered granular materials have gained considerable interest in recent years. For this substance, the primary design variable is grain shape. Optimizing grain form to achieve a macroscopic property is difficult due to the infinite-dimensional function space particle shape inhabits. Nonetheless, by parameterizing morphology the dimension of the problem can be reduced. In this work, we study the effects of both intuitive and machine-picked shape descriptors on granular material properties. First, we investigate the effect of classical shape descriptors (roundness, convexity, and aspect ratio) on packing fraction ϕ and coordination number Z. We use a genetic algorithm to generate a uniform sampling of shapes across these three shape parameters. The shapes are then simulated in the level set discrete element method. We discover that both ϕ and Z decrease with decreasing convexity, and Z increases with decreasing aspect ratio across the large sampling of morphologies—including among highly non-convex grains not commonly found in nature. Further, we find that subtle changes in mesoscopic properties can be attributed to a continuum of geometric phenomena, including tessellation, hexagonal packing, nematic order and arching. Nonetheless, such descriptors alone can not entirely describe a shape. Thus, we find a set of 20 descriptors which uniquely define a morphology via deep generative models. We show how two of these machine-derived parameters affect ϕ and Z. This methodology can be leveraged for topology optimization of granular materials, with applications ranging from robotic grippers to materials with tunable mechanical properties.
  • Kadau, Dirk; Schwesig, Dominik; Theuerkauf, Jörg; et al. (2006)
    Granular Matter
  • Third, J.R.; Scott, D.M.; Scott, S.A.; et al. (2011)
    Granular Matter
  • Mani, Roman; Kadau, Dirk; Herrmann, Hans J. (2013)
    Granular Matter
    We show how liquid migrates in sheared unsaturated granular media using a grain scale model for capillary bridges. Liquid is redistributed to neighboring contacts after rupture of individual capillary bridges leading to redistribution of liquid on large scales. The liquid profile evolution coincides with a recently developed continuum description for liquid migration in shear bands. The velocity profiles which are linked to the migration of liquid as well as the density profiles of wet and dry granular media are studied.
  • Roeck, Michael; Morgeneyer, Martin; Schwedes, Jörg; et al. (2008)
    Granular Matter
  • Third, James R.; Scott David M.; Lu, G.; et al. (2015)
    Granular Matter
    The axial dispersion of approximately monosized particles in rolling mode in rotating cylinders with bulk flow is examined using a Monte Carlo model and discrete element method (DEM) simulations. The Monte Carlo model predicts that the mean square displacement relative to the mean axial displacement of the bed undergoes oscillations in time. The nature of these oscillations depends on the fill level of the cylinder and the extent of particle mixing during avalanches. When the cylinder is half full the Monte Carlo model predicts undamped oscillations, whereas a filling fraction of 0.26 produces oscillations whose amplitude decreases with time. If mixing during avalanches is assumed to be perfect then the oscillations occur about a linear increase with time. In contrast, if it is assumed that the particles do not mix during avalanching, the oscillations occur about an increase with time which has a gradient which increases with time. There is good qualitative agreement between the Monte Carlo model with perfect mixing and the DEM when the filling fraction is 0.26. For a filling fraction of 0.5 the DEM data show oscillations about a faster than linear increase with time.
  • Lu, Guang; Third, James R.; Müller, Christoph R. (2017)
    Granular Matter
Publications 1 - 10 of 51