Cone crusher modelling and simulation using DEM
AUTHOR(S)
C. M. Evertsson, J. Quist
PUBLISHER
Elsevier
SOURCE
Minerals Engineering
YEAR
ABSTRACT
Compressive crushing has been proven to be one of the most energy efficient principles for breaking rock particles (Schönert, 1979). In this paper the cone crusher, which utilizes this mechanism, is investigated using the discrete element method (DEM) and industrial scale experiments. The purpose of the work is to develop a virtual simulation environment that can be used to gain fundamental understanding regarding internal processes and operational Compressive crushing has been proven to be one of the most energy efficient principles for breaking rock particles (Schönert, 1979). In this paper the cone crusher, which utilizes this mechanism, is investigated using the discrete element method (DEM) and industrial scale experiments. The purpose of the work is to develop a virtual simulation environment that can be used to gain fundamental understanding regarding internal processes and operational responses. A virtual crushing platform can not only be used for understanding but also for development of new crushers and for optimisation purposes.Rock particles are modelled using the bonded particle model (BPM) and laboratory single particle breakage tests have been used for calibration. The industrial scale experiments have been conducted on a Svedala H6000 cone crusher operated as a secondary crushing stage. Two different close side settings have been included in the analysis and a high speed data acquisition system has been developed and used to sample control signals such as pressure and power draw in order to enable detailed comparison with simulation results. The crusher has been simulated as a quarter section with a batch of breakable feed particles large enough to achieve a short moment of steady state operation. Novel methods have been developed to estimate the product particle size distribution using cluster size image analysis. The results show a relatively good correspondence between simulated and experimental data, however further work would be need to identify and target the sources of observed variation and discrepancy between the experiments and simulations.
KEYWORDS
erosion, fluidization, heat transfer, large eddy simulation