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An efficient sphere-packing algorithm named hierarchical generation method (HGM) is developed. The method is capable of efficiently generating spheres with a specific size distribution in a given geometric domain. Moreover, an improved contact algorithm for contact detection between spherical discrete elements and hexahedron finite elements (INTS) is presented. The algorithm is also suitable for simulating complex wheel–sand interactions. By using the developed algorithm, the running behaviors of a chevron tread-pattern wheel on a sand bed are simulated. The sand bed model is established by HGM and wheel–sand interactions are simulated using INTS. Numerical results validate the feasibility of the proposed method in the simulation of wheel–sand interactions.

Geotechnical systems often examine interactions that occur between continuum bodies and granular soils. The systems and interactions can be accurately simulated by using multiscale coupling approaches. The model for the continuum bodies is often constructed into a mesh. The meshing, however, is time consuming for a huge spatial system and if distorted is subject to adjustments. A mesh-free approach can be used to eliminate these drawbacks. In this study, a mesh-free approach for simulating continuum–granular systems is presented. This approach combines element-free Galerkin (EFG) and discrete element (DE) methods to approximate the interactions. The capabilities of the coupled EFG–DE method are validated through its solving two example problems: the cantilever beam–disc system and Cundall’s Nine Disc Test. The proposed approach appears to be an efficient and promising tool to model multiscale, multibody contacting problems.

A parallel computational strategy based on a distributed-memory environment is presented for simulating combined finite-discrete element systems comprising a large number of separate bodies. An explicit central difference scheme is used for the temporal integration of the governing equations. Some key issues, such as partitioning algorithms, load balance schemes and contact handling methods are discussed. A dual-level domain decomposition strategy is proposed to perform the dynamic domain decomposition. An implementation of this proposed strategy on cluster computing systems is described. MPI is adopted as the message passing library in this implementation. Numerical examples show that this implementation is suitable for simulating large scale problems. A dragline bucket filling model with 3 million degrees of freedom is built to demonstrate the parallel efficiency and scalability on a PC cluster.