Modeling the Multiphase Flow in Hydrocyclones Using the Coarse-Grained Volume of Fluid—Discrete Element Method and Mixture-Discrete Element Method Approaches

Local Percolation of a Binary Particle Mixture in a Rectangular Hopper with Inclined Bottom during Discharging

To reveal the local percolation characteristics of a binary particle mixture in a rectangular hopper with inclined bottom, the discrete element method (DEM) is used to simulate the discharging process. A local percolation evaluation method is proposed, and the percolation strength grid maps are drawn. The effects of geometric parameters, particle properties, and interaction parameters on percolation are investigated. Apart from the free surface, percolation is mainly concentrated near the wall and at the bottom. With the increase in the orifice width, the average local percolation strength index (ALPSI) of the near-wall region increases and that of the bottom region decreases. The effect of the angle on percolation in the near-wall region can be ignored. The effect of friction on local percolation is significant. Increasing the fine particle mass fraction and reducing the difference in particle size can effectively avoid percolation.

Possibilities and Limits of Computational Fluid Dynamics-Discrete Element Method Simulations in Process Engineering: A Review of Recent Advancements and Future Trends

Fluid-solid systems play a major role in a wide variety of industries, from pharmaceutical and consumer goods to chemical plants and energy generation. Along with this variety of fields comes a diversity in apparatuses and applications, most prominently fluidized and spouted beds, granulators and mixers, pneumatic conveying, drying, agglomeration, coating, and combustion. The most promising approach for modeling the flow in these systems is the CFD-DEM method, coupling computational fluid dynamics (CFD) for the fluid phase and the discrete element method (DEM) for the particles. This article reviews the progress in modeling particle-fluid flows with the CFD-DEM method. A brief overview of the basic method as well as methodical extensions of it are given. Recent applications of this simulation approach to separation and classification units, fluidized beds for both particle formation and energy conversion, comminution units, filtration, and bioreactors are reviewed. Future trends are identified and discussed regarding their viability.

Trends in Modeling, Design, and Optimization of Multiphase Systems in Minerals Processing

Multiphase systems are important in minerals processing, and usually include solid–solid and solid–fluid systems, such as in wet grinding, flotation, dewatering, and magnetic separation, among several other unit operations. In this paper, the current trends in the process system engineering tasks of modeling, design, and optimization in multiphase systems, are analyzed. Different scales of size and time are included, and therefore, the analysis includes modeling at the molecular level (molecular dynamic modeling) and unit operation level (e.g., computational fluid dynamic, CFD), and the application of optimization for the design of a plant. New strategies for the modeling, design, and optimization of multiphase systems are also included, with a strong focus on the application of artificial intelligence (AI) and the combination of experimentation and modeling with response surface methodology (RSM). The integration of different modeling techniques such as CFD with discrete element simulation (DEM) and response surface methodology (RSM) with artificial neural networks (ANN) is included. The paper finishes with tools to study the uncertainty, both epistemic and stochastic, based on uncertainty and global sensitivity analyses, which is present in all mineral processing operations. It is shown that all of these areas are very active and can help in the understanding, operation, design, and optimization of mineral processing that involves multiphase systems. Future needs, such as meso-scale modeling, are highlighted.