A coupled approach of discrete element method and pore network model (DEM-PNM) is developed for simulating particle–fluid flow. By this approach, the particle/solid flow is described at a particle scale by DEM and the fluid flow is described at a pore scale by PNM. The coupling scheme between DEM and PNM and the boundary conditions for realizing particle–fluid flows under different conditions are explicitly introduced. The capability is examined in three systems: a dynamic cell, a gas-fluidized bed, and a packed bed with lateral gas injection. The simulated results by the DEM-PNM approach agree with those results by either DEM-LBM (lattice Boltzmann method) approach or experiments. In particular, the simulated reasonable flow patterns in gas fluidization and lateral gas injection demonstrate the applicability of the proposed approach to complex particle–fluid flow. However, the current model presents less accuracy in dilute flow region and does not consider some important factors, which should be further improved in the future.

Discrete particle simulation can explicitly consider interparticle forces and obtain microscopic properties of the fluidized cohesive particles, but it is computationally expensive. It is thus pivotal to link the microscopic discrete properties to the macroscopic continuum description of the system for large scale applications. This work studies the fluidization of cohesive particles through the coupled computational fluid dynamics and discrete element method (CFD-DEM). First, discrete CFD-DEM results show the increased particle cohesion leads to the severe particle agglomeration which affects the fluidization quality significantly. Then, continuum properties are attained by a weighted time-volume averaging method, showing that tensile pressure becomes significant as particle cohesion increases. By incorporating Rumpf correlation into the solid pressure equation, the tensile pressure could be predicted consistently with the averaged CFD-DEM results for different particle cohesion. Finally, those overall steady averaged properties of the bed are obtained for understanding the general macroscopic properties of the system.

The packing of cohesive particles is of paramount importance in many industries because the packing structure is closely related to process performance. A general relation between packing density and interparticle force was previously proposed based on packing structures formed without dynamic fluid flows. Its universality is examined here in two different packings, formed in settling and defluidization of static and dynamic fluids, respectively. First, it is shown that the packings of the same particles formed by two different methods have different structures because of different impact-induced pressures. Nevertheless, a one-to-one relationship between packing density and structural properties still holds regardless of the different packing methods, and the force distribution in those packings obeys similar rules. Finally, the packing densities obtained by the different methods are demonstrated to be universally correlated with the ratio of the interparticle force to the effective gravity. These findings indicate that different phenomena of particulate systems at a macro- or meso-scale may share similar microscopic origins, with the interparticle force playing a crucial role.

Understanding the relationship between a fluid flow and the structural properties of a bed is important for various industrial applications and a proper description of particle-fluid flow. This work presents a pore-scale study of fluid flow through randomly packed beds by a network model. The model incorporates the inertial effect and thus can be applied to flows of high Reynolds numbers. The results show the structure heterogeneity associated with the connection of pores is important in determining the distribution of fluid flow. The statistical distribution of normalized drag forces on individual particles is Gaussian, related to the statistical distribution of pore properties. The mean drag force of a bed by the pore-scale model agrees well with that from a previous study by the lattice-Boltzmann method. These findings support the application of the pore network model for simulating particle-fluid flows under a wider range of Reynolds numbers.

Bed structure is important to heat and mass transfer in fluidization. This study investigates solid structural transition for cohesive particles by the combined approach of computational fluid dynamics and discrete element method, supported by Voronoi tessellation. Macroscopic behaviors of fluidized beds are first discussed in connection with microscopic structural transitions. Then, the properties of Voronoi polyhedra are analyzed at both bed and particle scales. In addition, the correlation of coordination number and porosity is examined at a particle scale, and their combined probability distribution is analyzed to identify dominant structure of particles in different flow regimes. Finally, an index is proposed as the ratio of coordination number and porosity to differentiate microscopic states of a particle. These findings should be useful for the study of flow, heat, and mass transfer in fluidized beds and for the understanding of solid-like to fluid-like transition of granular materials.