Discrete Element Methods

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Obtaining a fundamental understanding of the underlying physics of granular systems is important both for academic interest and industrial applications. Experimental measurements in full three-dimensional (3D) large industry scale granular system are complicated and expensive. Computational techniques such as the Discrete Element Method (DEM) can potentially be applied as a tool to provide understanding granular machine systems dynamics, virtual equipment design and evaluation of machine performance. DEM is used for applications like mining, post-harvest, soil-tool interaction, mixing and milling and geotechnical applications (Boac et al., 2014; Grima, Fraser, and Hastie, 2011).
Discrete Element Method (DEM) is a numerical method for simulating
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Material bulk engineering properties such as angle of repose, bulk density, grain to grain angle of internal friction and cohesion can be easily be measured from laboratory tests and related to grain-machine interaction systems responses where the micro parameters in DEM models are developed using particle-particle friction, particle-geometry friction and the particle density to simulate material behavior (Asaf et al., 2007). The particle size and shape distribution are also considered to be input DEM parameters. In DEM, spherical particles are usually preferred because of the efficiency of contact detection. However, when using this type of particles, the bulk friction of the assembly is usually too low compare to real material. There are two methods to increase the bulk friction which can be used separately or in combination. One method is to include contact rolling resistance and the other is to make use of non-spherical particles (Lu, …show more content…
One is to direct micro parameters measurement method in which the material micro properties are directly measured. Where some of these parameters are easy to measure, others are very difficult to determine. The other approach is inverse calibration method in which macro parameters are measured and by simulating the same application using DEM, the micro parameters are calibrated to obtain closest results to the measured macro parameters in the experiment (Marigo and Stitt, 2015). Using second approach may cause the micro parameters to lose their physical meaning. Where in the first approach the exact shape and size presentation of the particles are required for simulation to get accurate results. Since in most industrial applications it is computationally expensive to simulate granular materials with accurate shape and size, the second method is chosen for this study. Comment- avoid using the word first and second. Explicitly use the words e.g. inverse calibration vs. direct micro-parameters

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