Projects per year
Abstract
Graphics processing unit (GPU)-based DEM combined with message passing interface (MPI) has been applied to large-scale handling and processing systems, including granular conveying, reclaiming, screening, ship loading, grab and screw unloading, and blast furnace top charging systems. The issues in terms of particle flow behaviour, particle-wall interaction/wall stress, particle energy dissipation, size segregation, and process efficiency, etc., are discussed. The results showed that for a belt conveying chute, wear became more severe at higher flow rates. In the reclaiming process, there was an increase in the digging resistance on the buckets with increasing bucket rotation speed. For the screening process, lower vibrating frequency lead to a higher screening efficiency, but also higher wall stresses. In a ship loading process, particle streams with a wide size distribution provided a significant cushioning effect on particle degradation, and when the dropping height reduces, the dissipated energy by particle-particle impacts greatly reduced. For a grab unloader, particle velocities became smaller with an increase in grab close time with tangential stresses only slightly reduced within the close time range considered. An increase of rotational speed of the bottom blades of a screw unloader indicated a higher unloading efficiency. A full blast furnace top charging process model was also developed. Size segregation was observed at different stages of the charging process. This paper demonstrated that GPU-based DEM can be successfully applied to the whole granular process chain of ironmaking related industries at different scales and provide guidelines for the key issues in different processes.
Original language | English |
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Pages (from-to) | 258-273 |
Number of pages | 16 |
Journal | Powder Technology |
Volume | 361 |
DOIs | |
Publication status | Published - 1 Feb 2020 |
Keywords
- GPU- DEM
- Granular handling and processing
- Ironmaking industry
- Large-scale
Projects
- 1 Finished
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ARC Research Hub for Computational Particle Technology
Yu, A., Zhao, D., Rudman, M., Jiang, X., Selomulya, C., Zou, R., Yan, W., Zhou, Z., Guo, B., Shen, Y., Kuang, S., Chu, K., Yang, R., Zhu, H., Zeng, Q., Dong, K., Strezov, V., Wang, G., Zhao, B., Song, S., Evans, T. J., Mao, X., Zhu, J., Hu, D., Pan, R., Li, J., Williams, S. R. O., Luding, S., Liu, Q., Zhang, J., Huang, H., Jiang, Y., Qiu, T., Hapgood, K. & Chen, W.
Australian Research Council (ARC), Jiangxi University of Science and Technology, Jiangsu Industrial Technology Research Institute, Fujian Longking Co Ltd, Baosteel Group Corporation, Hamersley Iron Pty Limited, Monash University, University of New South Wales (UNSW), University of Queensland , Western Sydney University (WSU), Macquarie University
31/12/16 → 30/12/21
Project: Research