scholarly journals 2D Image-based calibration of rolling resistance in 3D discrete element models of sand

2021 ◽  
Author(s):  
Marcos Arroyo ◽  
◽  
Riccardo Rorato ◽  
Marco Previtali ◽  
Matteo Ciantia ◽  
...  
Keyword(s):  
Discrete Element Method ◽  
Particle Shape ◽  
Rolling Resistance ◽  
Discrete Element ◽  
Spherical Particles ◽  
Shape Effects ◽  
Element Method

Contact rolling resistance is the most widely used method to incorporate particle shape effects in the discrete element method (DEM). The main reason for this is that such approach allows for using spherical particles hence offering substantial computational benefits compared to non-spherical DEM models. This paper shows how rolling resistance parameters for 3D DEM models can be easily calibrated with 2D sand grain images.

scholarly journals Effect of the integration scheme on the rotation of non-spherical particles with the discrete element method

2019 ◽  
Vol 6 (4) ◽  
pp. 545-559 ◽  
Author(s):  
Joaquín Irazábal ◽  
Fernando Salazar ◽  
Miquel Santasusana ◽  
Eugenio Oñate
Keyword(s):  
Discrete Element Method ◽  
Discrete Element ◽  
Spherical Particles ◽  
Integration Scheme ◽  
Element Method

Surface Lunar Soil Excavation Simulation Based on Three-Dimensional Discrete Element Method

2013 ◽  
Vol 376 ◽  
pp. 366-370
Author(s):  
Hui Gao ◽  
Da Wei Zhang ◽  
Bin Liu ◽  
Long Chen Duan
Keyword(s):  
Discrete Element Method ◽  
Three Dimensional ◽  
Lunar Soil ◽  
Discrete Element ◽  
Spherical Particles ◽  
Lunar Exploration ◽  
The Earth ◽  
Large Numbers ◽  
Soil Excavation ◽  
Element Method

One of the important objectives of lunar exploration is to obtain the lunar soil samples. However, the sampling process is very different from that on the Earth due to special characteristics of the lunar soil and surface environment. In order to ensure that the lunar exploration and sampling are successful, large numbers of ground experiments and computer simulations must be taken. In this paper, the surface lunar soil excavation simulation is investigated by three-dimensional discrete element method (DEM). It is implemented based on the open source LIGGGHTS, which takes the lunar soil as spherical particles. The interaction between the excavation tool and lunar soil is demonstrated. The excavation force and torque have also been calculated in real time. Moreover, the comparison of the excavation in different environments between the Earth and Moon corresponding to their different gravity accelerations was done. This paper shows that three-dimensional discrete element method can be used for the surface lunar soil excavation simulation and can provide important reference results for actual operations.

2716 New method for considering particle shape in Discrete Element Method

2007 ◽  
Vol 2007.20 (0) ◽  
pp. 621-622
Author(s):  
Masatoshi AKASHI ◽  
Hiroshi MIO ◽  
Atsuko SHIMOSAKA ◽  
Yoshiyuki SHIRAKAWA ◽  
Jusuke HIDAKA ◽  
...  
Keyword(s):  
Discrete Element Method ◽  
Particle Shape ◽  
Discrete Element ◽  
New Method ◽  
Element Method

scholarly journals Comparison between O(n2) and O(n) neighbor search algorithm and its influence on superlinear speedup in parallel discrete element method (DEM) for complex-shaped particles

2018 ◽  
Vol 35 (6) ◽  
pp. 2327-2348 ◽  
Author(s):  
Beichuan Yan ◽  
Richard Regueiro
Keyword(s):  
Discrete Element Method ◽  
Particle Shape ◽  
Search Algorithm ◽  
Discrete Element ◽  
Search Algorithms ◽  
Content Type ◽  
Neighbor Search ◽  
Shape Complexity ◽  
Superlinear Speedup ◽  
Element Method

Purpose This paper aims to present performance comparison between O(n2) and O(n) neighbor search algorithms, studies their effects for different particle shape complexity and computational granularity (CG) and investigates the influence on superlinear speedup of 3D discrete element method (DEM) for complex-shaped particles. In particular, it aims to answer the question: O(n2) or O(n) neighbor search algorithm, which performs better in parallel 3D DEM computational practice? Design/methodology/approach The O(n2) and O(n) neighbor search algorithms are carefully implemented in the code paraEllip3d, which is executed on the Department of Defense supercomputers across five orders of magnitude of simulation scale (2,500; 12,000; 150,000; 1 million and 10 million particles) to evaluate and compare the performance, using both strong and weak scaling measurements. Findings The more complex the particle shapes (from sphere to ellipsoid to poly-ellipsoid), the smaller the neighbor search fraction (NSF); and the lower is the CG, the smaller is the NSF. In both serial and parallel computing of complex-shaped 3D DEM, the O(n2) algorithm is inefficient at coarse CG; however, it executes faster than O(n) algorithm at fine CGs that are mostly used in computational practice to achieve the best performance. This means that O(n2) algorithm outperforms O(n) in parallel 3D DEM generally. Practical implications Taking for granted that O(n) outperforms O(n2) unconditionally, complex-shaped 3D DEM is a misconception commonly encountered in the computational engineering and science literature. Originality/value The paper clarifies that performance of O(n2) and O(n) neighbor search algorithms for complex-shaped 3D DEM is affected by particle shape complexity and CG. In particular, the O(n2) algorithm outperforms the O(n) algorithm in large-scale parallel 3D DEM simulations generally, even though this outperformance is counterintuitive.

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