The calculation of mineral sizers productivity in China is mostly based on the structure and motion parameters of mineral sizers, without considering the effect of material properties on mineral sizers productivity. In this paper, a virtual prototyping method based on EDEM for mineral sizers productivity research is presented. Based on the material characteristics of mine users, various factors affecting mineral sizers productivity are analyzed and studied, which provides a reference for mineral sizers design and selection.
Mineral sizers as the core equipment of mobile crushing station and semi-mobile crushing station, its design theory and manufacturing technology have been mastered by foreign companies. As for the calculation of mineral sizers productivity, most of the domestic data are derived from structure and motion parameters, without considering the influencing factors such as material properties and particle size distribution, resulting in a large error in the calculation results. Based on EDEM, a virtual prototype research method for mineral sizers productivity is presented. The factors that affect productivity are analyzed according to the material characteristics of mine users, which provides a reference for design and selection. 1 Rock sampling and calibration
In order to ensure the accuracy of simulation, it is necessary to calibrate the simulation parameters. In the simulation research based on the discrete element method, the parameters of the rock model include the macroscopic physical properties and the microscopic mechanical properties of the rock. Macroscopic physical property parameters refer to Poisson's ratio, density, shear modulus, collision recovery coefficient, static friction factor and rolling friction factor of rocks: The mechanistically property parameters of rock refer to the parameters of the inter granular interaction model in the discrete element model based on the discrete element method, including unit area of inter granular interaction bond, normal stiffness, shear stiffness, normal ultimate strength, shear ultimate strength and radius of interaction bond. Both macroscopic physical property parameters and mechanistically property parameters need to be calibrated by field sampling and testing in discrete element environment. According to the requirements and working principles of the axial compression test, the simplified model of the testing machine was established according to the standard rock sample size. FIG. 1 shows the discrete element simulation model of the axial compression test.

Combined with the characteristics of discrete element software, uni axial compression test was carried out, and the software was set to load at 0.05ms, and then the stress situation of the upper pressure plate during the whole test process was extracted, and the compressive strength of the rock was calculated. FIG. 2 and 3 show the failure diagram of the sample in the test and the loading curve of the upper pressure plate respectively. For each group of tests, there is a maximum force F when the force analysis of the upper pressure plate is carried out. x, the force area of the specimen is the top surface area of its cylinder A, thus the compressive strength of the specimen max 1) A is obtained through repeated simulation until the failure form and compressive strength σ of the discrete element simulation model of the material are consistent with the uni axial compression test results of the sampled material. On this basis, the discrete element material simulation model mineral sizers is established.

2 The simulation scheme classifies the materials according to their compressive strength, which are divided into two categories: low compressive strength materials (1) and high compressive strength materials (1). The high compressive strength material should have a compressive strength of about 10MPa: the low compressive strength material should have a compressive strength of about 2MPa. Have a large feed size span and complex feed conditions. Due to the limitations of the discrete element method, the feed size must be simplified." Firstly, the feed particle size of 0~1800mm was dispersed into A limited number of particle size groups, and then the specific gravity of the material in each particle size group was calculated according to the particle size distribution function. Finally, the middle particle size of each particle size group was modeled, and the material larger than the size of a certain type mineral sizers outlet was simulated according to two particle size distributions, A and B.


3 Modeling and simulation
The simulation model is established and the simulation process is analyzed. Each group of simulation is a complete working process. First of all, the stacking process of the material in the tank is completed, and then the material is unloaded by the plate conveyor. The material will flow downward due to the action of gravity, enter the crushing chamber, and be broken and discharged under the action of the tooth roller to get the product. The modeling and simulation processes are shown in FIG. 6 and 7 respectively, and the simulation results are shown in FIG. 8-10. In the figure, H is the high compressive strength material; L is the low compressive strength material; A is the A-type particle size distribution; B is the B-type particle size distribution; 15 indicates that the gear roll speed is 15rmn; 1875 indicates that the gear roll speed is 18.75rmin; 21 indicates that the gear roll speed is 21rmin.