Assessing mixing characteristics of particle-mixing and granulation devices

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The mixing of particulates such as powders is an important process in many industries including pharmaceuticals, plastics, household products (such as detergents) and food processing. The quality of products depends on the degree of mixing of their constituent materials which in turn depends on both geometric design and operating conditions. Unfortunately, due to lack of understanding of the interaction between mixer geometry and the granular material, limited progress has been made in optimizing mixer design. The discrete element method (DEM) is a computational technique that allows particle systems to be simulated and mixing to be predicted. Simulation is an effective way of acquiring information on the performance of different mixers that is difficult and/or expensive to obtain using traditional experimental approaches. Here we demonstrate how DEM can be used to unravel flow dynamics and assess mixing in several different types of devices. These devices used for mixing and/or granulation of particulates, are classified broadly as gravity controlled, bladed and high shear. We also explore the role of particle shape in mixing performance and use DEM to test whether Froude number scaling is suitable for predicting scale performance of rotating mixers. The mixing of particulates such as powders is an important process in many industries including pharmaceuticals, plastics, household products (such as detergents) and food processing. The quality of products depends on the degree of mixing of their constituent materials which in turn depends on both Geometric design and operating conditions. Unfortunately, due to lack of understanding of the interaction between mixer geometry and the granular material, limited progress has been made in optimizing mixer design. The discrete element method (DEM) is a computational technique that allows particle systems to be simulated and mixing to be predicted. Simulation is an effective way of acquiring information on the performance of different mixers that is difficult and / or expensive to obtain using traditional experimental approaches. Here we demonstrate how DEM can be used to unravel flow dynamics and assess mixing in several different types of devices. These devices used for mixing and / or granul We also explore the role of particle shape in mixing performance and use DEM to test whether Froude number scaling is suitable for predicting scale performance of rotating mixers.
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