Issue |
EPJ Web Conf.
Volume 140, 2017
Powders and Grains 2017 – 8th International Conference on Micromechanics on Granular Media
|
|
---|---|---|
Article Number | 03071 | |
Number of page(s) | 4 | |
Section | Granular flow | |
DOI | https://doi.org/10.1051/epjconf/201714003071 | |
Published online | 30 June 2017 |
https://doi.org/10.1051/epjconf/201714003071
DEM GPU studies of industrial scale particle simulations for granular flow civil engineering applications
1 IMT Lille Douai, Univ. Lille, EA 4515 - LGCgE – Laboratoire de Génie Civil et géoEnvironnement, départment Génie Civil & Environnemental, F-59000 Lille, France
2 Research Center Pharmaceutical Engineering, GmbH, Graz, Austria
3 Centre for Asset and Integrity Management, University of Pretoria, Pretoria, 0086, South Africa
* e-mail: patrick.pizette@mines-douai.fr
Published online: 30 June 2017
The use of the Discrete Element Method (DEM) for industrial civil engineering industrial applications is currently limited due to the computational demands when large numbers of particles are considered. The graphics processing unit (GPU) with its highly parallelized hardware architecture shows potential to enable solution of civil engineering problems using discrete granular approaches. We demonstrate in this study the pratical utility of a validated GPU-enabled DEM modeling environment to simulate industrial scale granular problems. As illustration, the flow discharge of storage silos using 8 and 17 million particles is considered. DEM simulations have been performed to investigate the influence of particle size (equivalent size for the 20/40-mesh gravel) and induced shear stress for two hopper shapes. The preliminary results indicate that the shape of the hopper significantly influences the discharge rates for the same material. Specifically, this work shows that GPU-enabled DEM modeling environments can model industrial scale problems on a single portable computer within a day for 30 seconds of process time.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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