Parametric Analysis of a Double Shaft, Batch-Type Paddle Mixer Using the Discrete Element Method (DEM)

To improve the understanding of the mixing performance of double shaft, batch-type paddle mixers, the discrete element method (DEM) in combination with a Plackett-Burman design of experiments simulation plan is used to identify factor significance on the system's mixing performance. Effects of several factors, including three material properties (particle size, particle density and composition), three operational conditions (initial filling pattern, fill level and impeller rotational speed) and three geometric parameters (paddle size, paddle angle and paddle number), were quantitatively investigated using the relative standard deviation (RSD). Four key performance indicators (KPIs), namely the mixing quality, mixing time, average mixing power and energy required to reach a steady state, were defined to evaluate the performance of the double paddle mixer. The results show that the material property effects are not as significant as those of the operational conditions and geometric parameters. In particular, the geometric parameters were observed to significantly influence the energy consumption, while not affecting the mixing quality and mixing time, showing their potential towards designing more sustainable mixers. Furthermore, the analysis of granular temperature revealed that the centre area between the two paddles has a high diffusivity, which can be correlated to the mixing time.

Automated summary

In order to enhance the understanding of double shaft, batch-type paddle mixers, the discrete element method (DEM) in conjunction with a Plackett-Burman design of experiments simulation plan is utilized to determine the significance of various factors on the system's mixing performance. The effects of multiple factors, including material properties, operational conditions, and geometric parameters, are quantitatively investigated using the relative standard deviation (RSD). The results indicate that the operational conditions and geometric parameters have a more significant impact on the mixing performance compared to material properties, particularly in terms of energy consumption and sustainability.