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This paper aims to construct smooth poly-ellipsoid shapes from synchrotron microcomputed tomography (SMT) images on sand and to develop a new discrete element method (DEM) contact detection algorithm.

Voxelated images generated by SMT on Colorado Mason sand are processed to construct smooth poly-ellipsoidal particle approximations. For DEM contact detection, cuboidal shape approximations to the poly-ellipsoids are used to speed up contact detection.

The poly-ellipsoid particle shape approximation to Colorado Mason sand grains is better than a simpler ellipsoidal approximation. The new DEM contact algorithm leads to significant speedup and accuracy is maintained.

The paper limits particle shape approximation to smooth poly-ellipsoids.

Poly-ellipsoids provide asymmetry of particle shapes as compared to ellipsoids, thus allowing closer representation of real sand grain shapes that may be angular and unsymmetric. When incorporated in a DEM for computation, the poly-ellipsoids allow better representation of particle rolling, sliding and interlocking phenomena.

Method to construct poly-ellipsoid particle shapes from SMT data on real sands and computationally efficient DEM contact detection algorithm for poly-ellipsoids.

The paper aims to introduce an efficient contact detection algorithm for smooth convex particles.

The contact points of adjacent particles are defined according to the common‐normal concept. The problem of contact detection is formulated as 2D unconstrained optimization problem that is solved by a combination of Newton's method and a Levenberg‐Marquardt method.

The contact detection algorithm is efficient in terms of the number of iterations required to reach a high accuracy. In the case of non‐penetrating particles, a penetration can be ruled out in the course of the iterative solution before convergence is reached.

The algorithm is only applicable to smooth convex particles, where a bijective relation between the surface points and the surface normals exists.

By a new kind of formulation, the problem of contact detection between 3D particles can be reduced to a 2D unconstrained optimization problem. This formulation enables fast contact exclusions in the case of non‐penetrating particles.

The purpose of this paper is to find a convenient contact detection algorithm in order to apply in distinct element simulation.

Taking the most computation effort, the performance of the contact detection algorithm highly affects the running time. The algorithms investigated in this study consist of Incremental Sort-and-Update (ISU) and Double-Ended Spatial Sorting (DESS). These algorithms are based on bounding boxes, which makes the algorithm independent of blocks shapes. ISU and DESS algorithms contain sorting and updating phases. To compare the algorithms, they were implemented in identical examples of rock engineering problems with varying parameters.

The results show that the ISU algorithm gives lower running time and shows better performance when blocks are unevenly distributed in both axes. The conventional ISU merges the sorting and updating phases in its naïve implementation. In this paper, a new computational technique is proposed based on parallelization in order to effectively improve the ISU algorithm and decrease the running time of numerical analysis in large-scale rock mass projects.

In this approach, the sorting and updating phases are separated by minor changes in the algorithm. This tends to a minimal overhead of running time and a little extra memory usage and then the parallelization of phases can be applied. On the other hand, the time consumed by the updating phase of ISU algorithm is about 30 percent of the total time, which makes the parallelization justifiable. Here, according to the results for the large-scale problems, this improved technique can increase the performance of the ISU algorithm up to 20 percent.

Develop a new three‐dimensional discrete element code (BLOKS3D) for efficient simulation of polyhedral particles of any size. The paper describes efficient algorithms for the most important ingredients of a discrete element code.

New algorithms are presented for contact resolution and detection (including neighbor search and contact detection sections), contact point and force detection, and contact damping. In contact resolution and detection, a new neighbor search algorithm called TLS is described. Each contact is modeled with multiple contact points. A non‐linear force‐displacement relationship is suggested for contact force calculation and a dual‐criterion is employed for contact damping. The performance of the algorithm is compared to those currently available in the literature.

The algorithms are proven to significantly improve the analysis speed. A series of examples are presented to demonstrate and evaluate the performance of the proposed algorithms and the overall discrete element method (DEM) code.

Long computational times required to simulate large numbers of particles have been a major hindering factor in extensive application of DEM in many engineering applications. This paper describes an effort to enhance the available algorithms and further the engineering application of DEM.

Contact detection for convex polygons/polyhedra has been a critical issue in discrete/discontinuous modelling, such as the discrete element method (DEM) and the discontinuous deformation analysis (DDA). The recently developed 3D contact theory for polyhedra in DDA depends on the so-called entrance block of two polyhedra and reduces the contact to evaluate the distance between the reference point to the corresponding entrance block, but effective implementation is still lacking.

In this paper, the equivalence of the entrance block and the Minkowski difference of two polyhedra is emphasised and two well-known Minkowski difference-based contact detection and overlap computation algorithms, GJK and expanding polytope algorithm (EPA), are chosen as the possible numerical approaches to the 3D contact theory for DDA, and also as alternatives for computing polyhedral contact features in DEM. The key algorithmic issues are outlined and their important features are highlighted.

Numerical examples indicate that the average number of updates required in GJK for polyhedral contact is around 6, and only 1 or 2 iterations are needed in EPA to find the overlap and all the relevant contact features when the overlap between polyhedra is small.

The equivalence of the entrance block in DDA and the Minkowski difference of two polyhedra is emphasised; GJK- and EPA-based contact algorithms are applied to convex polyhedra in DEM; energy conservation is guaranteed for the contact theory used; and numerical results demonstrate the effectiveness of the proposed methodologies.

We present an algorithm for contact resolution that is valid for a wide variety of polygonal two dimensional shapes and is of linear computational complexity. The algorithm is designed for use in discrete element analysis of granular and multibody systems exhibiting discontinuous behaviour. Contact detection usually consists of a spatial sorting phase and a contact resolution phase. The spatial sorting phase seeks to avoid an all‐to‐all body comparison by culling the number of objects which are potential contactors of a given object. The contact resolution phase resolves the details of the contact between two given objects. The algorithm presented here (called DFR) addresses the contact resolution phase and is applicable to convex geometries and to a restricted set of concave geometries. Examination of the algorithm establishes an upper bound linear computational complexity, of order O(N), with respect to the number of points (N) used to define the object boundary. The DFR algorithm is combined with a modified heapsort algorithm for spatial sorting of M bodies which has complexity O(M log M) and is applied to a baseline granular simulation problem to test its efficiency.

When simulating the behaviour of granular assemblies and multi‐body systems using a discrete element analysis, the shape representation of the bodies and the contact detection algorithm greatly influence the flexibility, accuracy and efficiency of the simulation. Several geometrical shape descriptors of two and three dimensional arbitrary rigid bodies are reviewed and a flexible 3‐D descriptor introduced. The aim is to identify appropriate shape descriptors which allow a variety of types of bodies to be investigated while ensuring accurate and efficient detection of inter‐particle contacts. Polygons/polyhedrons, and continuous and discrete function representations are examined. The investigation favours discrete representations due to their efficiency and flexibility, but illustrates the elegance and efficiency of using a continuous function representation, e.g. a superquadric, to generate the discrete representation and simplify the contact detection process.

Presents a new contact detection algorithm based on double‐ended spatial sorting (DESS) that is insensitive to variations in object size. It was developed to address the problems that arise when objects with non‐spherical geometry and non‐uniform sizes are simulated using discrete element techniques. The algorithm is applicable to general spatial reasoning problems. While techniques based on spatial hashing (sometimes called bining methods) perform well for objects of similar size, they degrade significantly when the objects vary in size. The DESS algorithm overcomes this problem by using a spatial sorting technique applied to both ends of the object’s projection along each orthogonal axis. Discrete element test simulations comparing DESS and spatial hashing (NBS) are detailed. The results demonstrate that when object sizes vary significantly (size ratios greater than 8:1), DESS outperforms NBS up to around 100,000 objects. It is noted, however, that the superior scaling properties of NBS will always outperform DESS for some large numbers of objects.

Contact interaction and contact detection (CD) remain key components of any discontinua simulations. The methods of discontinua include combined finite-discrete element method (FDEM), discrete element method, molecular dynamics, etc. In recent years, a number of CD algorithms have been developed, such as Munjiza–Rougier (MR), Munjiza–Rougier–Schiava (MR-S), Munjiza-No Binary Search (NBS), Balanced Binary Tree Schiava (BBTS), 3D Discontinuous Deformation Analysis and many others. This work aims to conduct a numerical comparison of certain algorithms often used in FDEM for bodies of the same size. These include MR, MR-S, NBS and BBTS algorithms.

Computational simulations were used in this work.

In discrete element simulations where particles are introduced randomly or in which the relative position between particles is constantly changing, the MR and MR-S algorithms present an advantage in terms of CD times.

This paper presents a detailed comparison between CD algorithms. The comparisons are performed for problem cases with different lattices and distributions of particles in discrete element simulations. The comparison includes algorithms that have not been evaluated between them. Also, two new algorithms are presented in the paper, MR-S and BBTS.

The purpose of this paper is to present a new method for the detection and resolution of the contact point between two ellipsoids. Numerical simulations of ellipsoidal particles in a rotary cylinder are also presented.

An algebraic condition is developed for the internal contact between two ellipsoids and an efficient contact detection algorithm for overlapping ellipsoids is implemented.

This method was found to have the advantages of effectiveness and speed in the detection and resolution of the contact point.

The dynamics of granular materials are of great importance in many industries dealing with powders and grains, such as pharmaceutical, chemical, and food industries. The main difficulty of such simulations is the excessive CPU time required for a large number of particles. In the discrete element method, contact detection between grains is the most expensive step in solving a nonlinear system for determination of the contact point, the normal vector and the overlap distance between ellipsoids. The numerical behavior and the optimization of the new algorithm presented in this paper are important also.