(673c) DEM Investigation of Adhesive Mixing of Fine and Coarse Particles: Dynamics of Collisional Mixing and Attachment | AIChE

(673c) DEM Investigation of Adhesive Mixing of Fine and Coarse Particles: Dynamics of Collisional Mixing and Attachment

Authors 

Dave, R. N. - Presenter, New Jersey Institute of Technology
Deng, X., New Jersey Institute of Technology
Zheng, K., New Jersey Institute of Technology
When small number of fine particles are mixed with coarser particles, they form ordered mixtures or what may be called adhesive mixtures. In this work, discrete element method (DEM) simulations are carried out to characterize the adhesive mixing process. The dynamic processes such as deagglomeration and adhesion of fine particles are investigated by analyzing fine-fine (FF) and coarse-fine (CF) particle contact numbers along with the mixing quality. The FF and CF contact numbers are used to quantify the deagglomeration and adhesion processes, respectively. The DEM simulation results showed that FF contact number decreases first and then reaches equilibrium; while CF contact number and mixing quality increase first and then reach equilibrium. Interestingly, the number of fine particles per coarse particle follows lognormal distribution. The time scales for equilibrium FF contact number and mixing quality are comparable, indicating that deagglomeration is the dominant factor for achieving a uniform adhesive mixture. This time scale increases with a larger ratio of fine particles and a higher surface energy. Collisional mixing dynamics provide a deeper insight into the adhesive mixing process. The results indicate that increasing surface energy of fine particles leads to worse mixing quality because the fine particles with high surface energy create such strong agglomerates that cannot be easily broken by the collision. Collision rate can dominate the mixing quality with the prerequisite that the collision energy is greater than the corresponding detachment energy of fine particles agglomerates. The experimental results validate that the modeling is suitable to describe the adhesive mixing process.

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