10 pág.

# DEM AS A TOOL FOR DESIGN AND OPTIMISATION OF MINERAL PROCESSING EQUIPMENT

Pré-visualização4 páginas

so the center of the finer middle stream falling from the impact plate is directly over the center of the bin, then equal amounts of the fines will fall into either side of the bin. The coarse material is mostly in the two outer streams falling from the impact plate. One stream falls into each hopper and so the amount and composition of coarse material in each hopper is essentially the same. The overall composition of the material in each hopper is then the same, (even though there are differences in the distribution of the coarse and fine within each hopper). If the impact plate is placed closer to the incoming conveyor then a larger fraction of the fines will fall into the closer hopper (the left one in Figure 7c) and the left hopper will have a finer composition than the right one. Conversely, if the impact plate is located further away then more of the finer material will fall into the far hopper (on the right in Figure 7c) and this will have a finer composition. The positioning of the impact plate is therefore critical as this determines the split of fine material between hoppers. We note here that extreme positions of the impact plate will also start to affect the split of the coarse material between hoppers. The sideways position of the impact plate is not important as long as the entire incoming stream is deflected by the plate. These observations have been made on the basis of one simulated configuration, but the general understanding obtained can be expected to apply for a range of belt speeds and tonnages and for variants of the conveyor and bin geometry. The critical aspects required to generate the composition variations are the asymmetric orientation of the incoming conveyor, the presence of an impact plate and the initially vertically segregated material on the incoming belt. CONCLUSIONS DEM simulations of applications relating to the storage, transport, sampling and separation of particulate solids have shown that: ! A broad variety of coarse particulate mineral processing equipment can be successfully modelled. ! Relevant information relating to the important issues for each of the types of equipment/processes can be predicted. This includes flow rates, segregation effects, particle degradation and damage to equipment for transport equipment; sample bias for sample cutters; segregation effects, flow rates and wall stresses for storage and reclaim equipment and separation efficiency for vibrating screen decks. ! Enhanced understanding of the particulate flows in the equipment and of the important issues for each case. ACKNOWLEDGEMENTS The author would like to acknowledge the contributions of Geoff Robinson to the development of the capability to analyse cross belt conveyor sampling over the last decade. Also acknowledged is the work of Phil Owen in performing the screw conveyor simulations. REFERENCES Barker, G. C., (1994), Computer simulations of granular materials, Granular Matter: An interdisciplinary approach, Ed. Anita Mehta, Springer-Verlag, NY. Campbell, C. S., (1990), Rapid Granular Flows, Annual Rev. Fluid Mech., Vol. 22, pp. 57-92. Cleary, P. W., (1998a), Predicting charge motion, power draw, segregation, wear and particle breakage in ball mills using discrete element methods'', Minerals Engineering, Vol. 11, pp. 1061-1080. Cleary, P. W., (1998b), Discrete Element Modelling of Industrial Granular Flow Applications, TASK. Quarterly - Scientific Bulletin, Vol. 2, pp. 385-416. Cleary, P. W., (2000), DEM simulation of industrial particle flows: Case studies of dragline excavators, mixing in tumblers and centrifugal mills, Powder Technology, Vol. 109, 83-104. Cleary, P. W., (2001a), Modelling Comminution Devices using DEM, Int. J. for Numer. Anal. Meth. Geomechan., Vol. 25, pp. 83-105. Cleary, P. W., (2001b), Charge behaviour and power consumption in ball mills: Sensitivity to mill operating conditions, liner geometry and charge composition, Int. J. Min. Processing, Vol. 63, 79-114, (2001). Cleary, P.W., Morrison, R., and Morrell, S., (2001), DEM validation for a scale model SAG mill, Proc. SAG 2001, pp. IV-191. Holst, J. M., Rotter, J. M., Ooi, J. Y., and Rong, G. H., (1999), Numerical modelling of silo filling. II: Discrete element analysis, J. Eng. Mech., Vol. 125, 94-110. Mishra, B. K., and Rajamani, R. J., (1992), The discrete element method for the simulation of ball mills, App. Math. Modelling, Vol. 16, pp. 598-604. Mishra, B. K., and Rajamani, R. K., (1994), Simulation of charge motion in ball mills. Part 1: Experimental verifications, Int. J. Mineral Processing, Vol. 40, pp. 171--186. Morrison, R., Cleary, P.W., and Valery, W., (2001), Comparing Power and Performance Trends from DEM and JK modelling'', Proc. SAG 2001, pp. IV-284. Rajamani, R. K., and Mishra, B. K., (1996), Dynamics of ball and rock charge in sag mills, Proc. SAG 1996, Department of Mining and Mineral Process Engineering, University of British Columbia. Ristow, G. H., (1994), Granular Dynamics: A review about recent Molecular Dynamics Simulations, Ann. Rev. of Comp. Phys., Vol. 1, pp. 275-308. Robinson, G. K., and Cleary, P. W., (1999), The Conditions for Sampling of Particulate Materials to be Unbiased - Investigation Using Granular Flow Modelling, Minerals Engineering, Vol. 12, 1101-1118. Schäfer, J., Dippel, S., and Wolf, D. E., (1996), Force schemes in simulation of granular material, J. Physique I France, Vol. 6, pp. 5. Walton, O. R., (1994), Numerical simulation of inelastic frictional particle-particle interaction, Chapter 25, Particulate two-phase flow, Ed. M. C. Roco, pp. 884-911.