Determining the relationship between the simulation duration by the discrete element method and the computer system technical characteristics
Keywords:discrete element method, computational system, algorithm, simulation time, computational resources
The object of this study is the relationship between the technical characteristics of a computing system and the duration of modeling the motion of particles of granular materials by the discrete element method. The scheme of the calculation algorithm is presented; its main stages are analyzed. A 3D model of a belt feeder and a mathematical model of particle motion were developed for calculations by the discrete element method in the EDEM 2017 environment. The physical and mechanical properties of bulk material are defined; the structural and technological parameters of equipment are determined. The parameters of the algorithm and computing system are analyzed. Those parameters are defined, the change of which does not affect the accuracy of calculations but can change the volume of computing resources used. These include the number of particles of loose material, the «grid» step, and the number of processor cores. The influence of these parameters on the duration of simulation was determined using a complete factor experiment.
Experimental studies have shown that for the duration of the simulation, the determining parameters are the number of particles and the number of processor cores. It was established that there is a linear relationship between the duration of the simulation and the number of particles. The regression equation is built, which makes it possible to predict the simulation time. It was also established that the software does not fully use all available computing resources; the maximum load on the processor when utilizing all available cores is 57 %. The use of RAM and disk subsystem almost did not change during simulation.
The results reported here make it possible to plan the use of computing resources for research using the discrete element method and to predict the simulation time
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