Dynamics of separation characteristics of sieving and flow classification processes

现有的干式分级模型是基于简化的，这阻碍了对分级设备在不同操作条件下的动态行为的充分描述。因此，本文将以时间分辨的方式研究逆流分级器--偏转轮分级器的动态行为。结果表明，现有的基于单个颗粒的离心力和摩擦力的模型需要扩展，以考虑颗粒-颗粒和颗粒-桨的碰撞。虽然在前两个资助期是以平稳行为为目标的，但在第三个时期，非稳态条件下的分离行为也将被包括在模型中，该模型将成为偏转轮分类器的完整动态表示的中心。除了粒子碰撞，该模型还将考虑条纹和围绕车轮运行的颗粒环，从而将特征时间常数(持有率)扩展到比预期高得多的值。通过将实验结果与DEM模拟结果进行比较，提取模型的输入参数，如恢复系数和有效粘性。

Existing models for dry classification are based on simplifications which hinder the adequate description of the dynamic behavior of the classifying apparatus under varying operational conditions. Therefore, the dynamic behavior of a counter current flow classifier, i.e. deflection wheel classifier, will be studied here in a time resolved manner. It was shown that the existing models, which are based on centrifugal and frictional forces on single particles, need to be extended in order to incorporate particle-particle and particle-paddle collisions. While in the first two funding periods the stationary behavior was targeted, in the third period also the separation behavior under non-steady conditions will be included in the model which will be at the center of a complete dynamic representation of the deflection wheel classifier. Besides particle collisions this model will also take into account streaks and a particulate ring, which is orbiting the wheel, thereby extending the characteristic time constants (hold-up) to much higher values than expected. By the comparison of the experimental results with DEM simulations the input parameters of the model, such as the coefficient of restitution and the effective viscosity, will be extracted.