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Estimation of particle rotation in fluidized beds by means of PTV

机译：通过PTV估计流化床中的颗粒旋转

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Fluidized bed granulation is a widely used process to produce pharmaceuticals, food and fertilizer. The achievable product quality, for example the uniformity of the formed layer or the size of the agglomerates, inherently depends on the particle dynamics in the bed. Generally, the solid phase velocity field is used to determine characteristic particle times (turn-over and residence time) in different zones of a spray fluidized bed. This information can be acquired using particle image velocimetry (PIV) together with digital image analysis (DIA) as for example in Borner et al. (2011,2013). In order to derive certain quantities, such as particle mass flow rates, the measurement results are averaged in space and time, which is directly associated with a loss of information. However, an alternative is available when using the Lagrangian particle description {particle trajectories and local particle velocities) in terms of particle tracking velocimetry (PTV). Particle velocities are estimated on the basis of identifying individual particles, leading to exact particle mass flow rates. There are known shortcomings with this method for dense particulate flows, in particular ambiguities during particle identification. These problems have been fixed to a certain extent, for example using colored tracer particles (Natarajan et al. 1995, Bendicks et al., 2011) or recognition of flow pattern (Capart et al., 2002). The former approach yields a low resolution, but ensures reasonable results for particle velocities and associated trajectories. Additionally, it is possible to obtain information concerning the particle rotation, when using traces with an adequate color pattern (e.g. Zimmermann et al., 2011). Therefore, we used half-page blackened tracer particles in order to estimate particle velocities and particle rotation simultaneously and unambiguously within 2D-fluidized bed. Solid mass flow rates and particle residence times can be derived from the local particle velocities. At the same time, the observation of discontinuous particle tracks together with the quantification of the particle rotation can be used to foster the insight and understanding of particle-particle contact and the associated momentum transfer in dense gas-solid multiphase flows. Eventually, we can obtain local particle collision rates and corresponding changes of normal and angular momentum of individual tracer pairs.
机译：流化床造粒是一种广泛使用的方法，用于生产药物，食品和肥料。可实现的产品质量，例如形成的层的均匀性或附聚物的尺寸固有地取决于床中的粒子动态。通常，固相速度场用于确定喷雾流化床的不同区域中的特征粒度（转圈和停留时间）。可以将该信息与数字图像分析（DIA）一起使用粒子图像VENOCIMETRY（PIV）来获取，例如在Borner等人中。 （2011,2013）。为了导出某些数量，例如粒子质量流量率，测量结果在空间和时间中平均，其直接与信息丢失相关联。然而，当在粒子跟踪速度（PTV）方面，使用拉格朗日粒子描述{粒子轨迹和局部粒子速度时，可以使用替代方案。基于识别单个颗粒，估计颗粒速度，导致精确的粒子质量流量。有这种方法存在已知的缺点，用于粒度颗粒流动，特别是在粒子识别期间的歧义。这些问题已经在一定程度上得到了一定程度，例如使用彩色示踪剂粒子（Natarajan等，1995，Bendicks等，2011）或识别流动模式（Capart等，2002）。前一种方法产生低分辨率，但确保颗粒速度和相关轨迹的合理结果。另外，当使用具有足够颜色图案的迹线时，可以获得有关粒子旋转的信息（例如，Zimmermann等，2011）。因此，我们使用了半页变黑的示踪剂颗粒，以便在2D流化床内同时和明确地估计粒子速度和颗粒旋转。固体物质流速和颗粒停留时间可以源自局部颗粒速度。同时，将不连续粒子轨道的观察与颗粒旋转的量化一起用于培养粒子粒子接触的见解和理解，并在致密气体固体多相流动中的相关动量转移。最终，我们可以获得当地的粒子碰撞速率和各个示踪成对的正常和角动量的相应变化。

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