A method for predicting the coalescence rate and coalescence strength of crystals under hygroscopicity
A technology of hygroscopic effect and coalescence rate, which is applied in the field of simulation analysis, can solve the problems of difficult to find, long detection time, and no simulation analysis of crystal coalescence rate and coalescence strength, etc., to improve accuracy and obtain experimental data quickly and easily. Effect
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Embodiment 1
[0038] In step (1), the spherical crystal particle A is selected, and its particle size distribution and shape characteristics are analyzed by a particle size and shape analyzer. According to its actual particle size distribution, the simulation parameters are simplified to 200, 350, 500, and 650 microns, and the number of particles in each particle size interval is set to 25; according to its spherical shape, see Figure 1A (a), can be simulated using the spherical particle model of DEM. See Figure 1B , input particle parameters (particle diameter, number, density, grouping, void ratio, contact properties) and boundary parameters (wall size, random parameters, contact properties between walls and particles) into the discrete element program, see Table 1 for details , and then output the distribution mode and contact property map of spherical particles, see 1C.
[0039] Table 1 DEM simulation parameter list of crystal A
[0040] parameter name
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Embodiment 2
[0058] In step (1), the cubic crystal particle B is selected, and its particle size distribution and shape characteristics are analyzed by a particle size and shape analyzer. According to its actual particle size distribution, the simulation parameters are simplified to 200, 300, 400, and 500 microns, and the number of particles in each particle size interval is set to 25; according to the shape of its cube, see Figure 2A (a), DEM can be used to simulate a cube composed of 8 spherical particles. See Figure 2B , input cubic particle parameters (irregular particle diameter, number, density, tensor, void ratio, contact properties) and boundary parameters (wall size, random parameters, contact properties between walls and particles) into the discrete element program, See Table 4 for details. The distribution pattern and contact property map of cubic particles can be output, see 2C.
[0059] Table 4 DEM simulation parameter table of crystal A
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