4.7 Article

Modeling granular material dynamics and its two-way coupling with moving solid bodies using a continuum representation and the SPH method

Journal

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.cma.2021.114022

Keywords

Granular material; Continuum representation; Smoothed particle hydrodynamics; Fluid-solid interaction; Two-way coupling; Elasto-plasticity

Funding

  1. National Science Foundation, US [CMMI1635004, CISE1835674]
  2. US Army Research Office [W911NF1910431, W911NF1810476]
  3. U.S. Department of Defense (DOD) [W911NF1810476] Funding Source: U.S. Department of Defense (DOD)

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A continuum approach for treating discrete granular flows is proposed and validated through experiments, tests, and numerical simulations. The implementation of this approach leverages GPU computing and is publicly available on GitHub.
We outline a continuum approach for treating discrete granular flows that holds across multiple scales: from experiments that focus on centimeter-size control volumes, to tests that involve landslides and large buildings. The time evolution of the continuum used to capture the granular dynamics is resolved in space via the smoothed particle hydrodynamics (SPH) method. The interaction between the granular material and immersed rigid bodies is posed and solved as a fluid-solid interaction (FSI) problem using boundary conditions enforcing (BCE) SPH particles rigidly attached onto the boundary of the body interacting with the granular material. A new penetration-based particle shifting technique (PPST) is proposed to enforce the particle regularity and thus a stable simulation. Several numerical experiments (angle of repose, ball drop, and cone penetration) are carried out to validate the accuracy of the proposed methodology. The approach is subsequently demonstrated in conjunction with a 3D landslide simulation and a plowing operation. The approach discussed has been implemented and can be used in an open source simulation platform publicly available on GitHub. The implementation leverages GPU computing. (C) 2021 Elsevier B.V. All rights reserved.

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