The design parameters of a mixing system have a major impact on the quality of the final product. Therefore, identifying the optimum parameters of mixing systems is highly relevant to various industrial processes dealing with particulate flows. However, the studies on the influences of the mixer’s design features are still insufficient. In this study, the Discrete Element Method (DEM) is used to examine the impact of paddle angle, width, and gap on the mixing performance of a twin paddle blender. The mixing performance and particle flow are assessed using the relative standard deviation (RSD) mixing index, velocity field, diffusivity coefficient, granular temperature, the force acting on particles, and the mixer’s power consumption. The mixing performance is highest for a paddle angle of 0° at the cost of the highest forces acting on particles. The paddle width is indicated as a critical factor for achieving better mixing quality. In contrast, the powder mixing efficiency and the mixer’s power consumption are not significantly affected by the paddle gap. The results regarding the power consumption denote that the mixer using the paddle angle of 60° has the minimum power consumption. Moreover, increasing the paddle width results in the enhancement of the mixer’s power consumption.

In this study, we have investigated the mixing kinetics and flow patterns of non-spherical particles in a horizontal double paddle blender using both experiments and the discrete element method (DEM). The experimental data were obtained using image analysis from a rotary drum containing cubical and cylindrical particles. Then, the experimental data were used in order to calibrate the DEM model. Using the calibrated DEM model, the effects of operating parameters such as vessel fill level, particle loading arrangement, and impeller rotational speed on the mixing performance were examined. The diffusivity coefficient was calculated to assess the mixing performance.

An in-depth analysis of the flow patterns and mixing dynamics in a twin-paddle blender with bi-disperse non-spherical particles was investigated using the discrete element method (DEM) and experiments. This study aimed to explore the mixing efficiency of a twin-paddle blender containing two different shapes of non-spherical particles. The study focussed on the demonstration of the applicability of the GPU-based DEM model. To achieve this, calibration tests were performed using a classical rotary drum to validate the accuracy of the DEM model. The next step was to examine the impact of various operating parameters on the mixing performance, such as impeller rotational speed. The relative standard deviation (RSD) was employed as a measure of mixing performance. Results revealed that the rotational speed of the impellers had a significant impact on the mixing performance.