Sizereduction systems have been extensively used in industry for many years. Nevertheless, reliable engi neering tools to be used to predict the comminution of particles are scarce. Computational fluid dynamics （CFD...Sizereduction systems have been extensively used in industry for many years. Nevertheless, reliable engi neering tools to be used to predict the comminution of particles are scarce. Computational fluid dynamics （CFD）discrete element model （DEM） numerical simulation may be used to predict such a complex phe nomenon and therefore establish a proper design and optimization model for comminution systems, They may also be used to predict attrition in systems where particle attrition is significant. Therefore, empirical comminution functions （which are applicable for any attrition/comminution process）, such as： strength distribution, selection, equivalence, breakage, and fatigue, have been integrated into the three dimensional CFDDEM simulation tool. The main drawback of such a design tool is the long computational time required owing to the large number of particles and the minute timestep required to maintain a steady solution while simulating the flow of particulate materials with very fine particles. The present study developed several methods to accelerate CFDDEM simulations： reducing the num ber of operations carried out at the singleparticle level, constructing a DEM grid detached from the CFD grid enabling a no binary search, generating a subgrid within the DEM grid to enable a no binary search for fine particles, and increasing the computational timestep and eliminating the finest particles in the simulation while still tracking their contribution to the process. The total speedup of the simulation process without the elimination of the finest particles was a factor of about 17. The elimination of the finest particles gave additional speedup of a factor of at least 18. Therefore, the simulation of a grinding process can run at least 300 times faster than the conventional method in which a standard no binary search is employed and the smallest particles are tracked.展开更多
文摘Sizereduction systems have been extensively used in industry for many years. Nevertheless, reliable engi neering tools to be used to predict the comminution of particles are scarce. Computational fluid dynamics （CFD）discrete element model （DEM） numerical simulation may be used to predict such a complex phe nomenon and therefore establish a proper design and optimization model for comminution systems, They may also be used to predict attrition in systems where particle attrition is significant. Therefore, empirical comminution functions （which are applicable for any attrition/comminution process）, such as： strength distribution, selection, equivalence, breakage, and fatigue, have been integrated into the three dimensional CFDDEM simulation tool. The main drawback of such a design tool is the long computational time required owing to the large number of particles and the minute timestep required to maintain a steady solution while simulating the flow of particulate materials with very fine particles. The present study developed several methods to accelerate CFDDEM simulations： reducing the num ber of operations carried out at the singleparticle level, constructing a DEM grid detached from the CFD grid enabling a no binary search, generating a subgrid within the DEM grid to enable a no binary search for fine particles, and increasing the computational timestep and eliminating the finest particles in the simulation while still tracking their contribution to the process. The total speedup of the simulation process without the elimination of the finest particles was a factor of about 17. The elimination of the finest particles gave additional speedup of a factor of at least 18. Therefore, the simulation of a grinding process can run at least 300 times faster than the conventional method in which a standard no binary search is employed and the smallest particles are tracked.
