Abstract
By modeling a group of neighboring real particles as a single coarse-grained particle (CGP), discrete particle method (DPM) is now capable of simulating industrial-scale particle-fluid systems. However, a systematic approach to determine the CGP properties and develop their interaction models is still lacking, which casts uncertainty on the predictivity of the method. In this study, collisions between predefined particle groups are analyzed to construct kernel functions for modeling the CGPs and then the model parameters are determined by equating the statistical properties of the CGPs and the real particles in the physical process studied. This approach is implemented for homogeneous cooling of granular gas, then demonstrated effective in simulating experimental fluidized beds.
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