TY - GEN
T1 - Application of DEM modelling to grinding processes
AU - Yang, R. Y.
AU - Jayasundara, C. T.
AU - Yu, A. B.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2015/3/2
Y1 - 2015/3/2
N2 - Understanding energy utilisation in grinding is critical to the process optimisation. In this paper, we demonstrated that the discrete element method (DEM) modelling, when combined with experimental measurements, can provide more realistic and reliable description of grinding processes. By incorporating particle grindability from experiments and energy condition from DEM simulations into a population balance model (PBM), we developed a multi-scale framework to predict mill performance. The model can be an invaluable tool in the design, control and optimisation of grinding processes.
AB - Understanding energy utilisation in grinding is critical to the process optimisation. In this paper, we demonstrated that the discrete element method (DEM) modelling, when combined with experimental measurements, can provide more realistic and reliable description of grinding processes. By incorporating particle grindability from experiments and energy condition from DEM simulations into a population balance model (PBM), we developed a multi-scale framework to predict mill performance. The model can be an invaluable tool in the design, control and optimisation of grinding processes.
KW - Discrete element modelling
KW - Grinding
KW - Population balance model
KW - Process optimisation
UR - https://www.scopus.com/pages/publications/84932111106
U2 - 10.1109/WCICA.2014.7053164
DO - 10.1109/WCICA.2014.7053164
M3 - 会议稿件
AN - SCOPUS:84932111106
T3 - Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
SP - 2765
EP - 2769
BT - Proceeding of the 11th World Congress on Intelligent Control and Automation, WCICA 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 11th World Congress on Intelligent Control and Automation, WCICA 2014
Y2 - 29 June 2014 through 4 July 2014
ER -