DEM Parameter Fuzzy Self-tuning Method For Granular Material

Rotary kilns, ball mills and other process equipments with rotating cylinder as main component are widely used in cement, metallurgical, pharmaceutical and chemical industries, play an extremely important role in national economic construction. The mixing process of the particles in the rotary kiln has great impact on the product quality and production efficiency. It is thus necessary to study on the mixing process of the particles in the rotary kiln. With the rapid development of high-performance computing technology, Discrete Element Method(DEM) becomes a powerful tool for the study of granular system in rotating cylinder process equipments.However, the DEM simulation results are sensitive to input parameters. Some important simulation parameters such as particle-particle friction coefficient and particle-wall friction coefficient cannot be measured directly. The friction coefficients used in DEM simulation generally is constantly adjusted manually to match the experiment observations. Such a process of parameter adjustment is time-consuming and somewhat subjective.In view of the above questions, this thesis took the particle system in rotating cylinder as the object, designed a DEM friction coefficients fuzzy self-tuning system, developed the corresponding software on Lab VIEW to achieve the DEM simulation friction coefficient automatically. The topic has high theoretical and practical value. The main achievements and achievements of the paper are:(1) Experimental set-up was established to mimic the the mixing process of particles in the rotary kiln equipment, then the corresponding DEM model for mixing process was established. The DEM simulation of the mixing process in the rotary drum was carried out based on the PFC3 D, then the influence of friction coefficients on simulation results was analyzed.(2) The variation trend of the repose angle in the rotary was analyzed and two characteristic response angles were defined. Then influence of friction coefficient on characteristic repose angle was studied.(3) A friction coefficient fuzzy self-tuning stategy and a fuzzy inference engine of DEM friction coefficient were proposed. The deviations of the characteristic response angles in the experiment and simulation were used as the input. The friction coefficients of particle-particle and particle-wall were calculated by fuzzy inference. A DEM friction coefficient fuzzy self-tuning software was developed based on Lab VIEW, including the interaction of simulation and experiment, the visualization of friction coefficients auto-tuning process.(4) 9 sets of testing experiments were carried out using the developed software. The stability and rapidity of this system was verified. With tuned friction coefficients, the simulation results were found to agree well with experimental result, demonstrating the effectiveness of the proposed methods in this work.