Multi-scale modeling of dense gas-particle flows

Dense gas-particle flows are encountered in a variety of industrially important processes for large scale production of fuels, fertilizers and base chemicals. The scale-up of these processes is often problematic, which can be related to the intrinsic complexities of these flows which are unfortunately not yet fully understood despite significant efforts made in both academic and industrial research laboratories. In dense gas-particle flows both (effective) fluid-particle and (dissipative) particle-particle interactions need to be accounted for, because these phenomena to a large extend govern the prevailing flow phenomena, i.e. the formation and evolution of heterogeneous structures. These structures have significant impact on the queality of the gas-solid contact and as a direct consequense thereof strongly affect the performance of the process. Due to the inherent complexity of dense gas-particles flows the authors have adopted a multi-scale modelling approach in which both fluid-particle and particle-particle interactions ca be properly accounted for. The idea is essentially that fundamental models, taking into account the relevant details of fluid-particle (lattice Boltzmann model) and particle-particle (discrete particle model) interactions, are used to develop closure laws to feed continuum models which can be used to compute the flow structures on a much larger (industrial) scale. Our multi-scale approach (figure) involves the lattice Boltzmann model, the discrete particle model and the continuum model based on the kinetic theory of granular flow. In this presentation the multi-scale modeling strategy for dense gas-partticle flows will be presented together with illustrative computational results. In addition, areas which need substantial further attention will be hightlighted

Flow structure formation and evolution in circulating gas-fluidised beds

The occurrence of heterogeneous flow structures in gas-particle flows seriously affects the gas-solid contacting and transport processes in high-velocity gas-fluidized beds. Particles do not disperse uniformly in the flow but pass through the bed in a swarm of clusters. The so-called core-annulus structure in the radial direction and S shaped axial distribution of solids concentration characterize the typical flow structure in the system. A computational study, using the discrete particle approach based on molecular dynamics techniques, has been carried out to explore the mechanisms underlying formation of the clusters and the core-annulus structure. Based on energy budget analysis including work done by the drag force, kinetic energy, rotational energy, potential energy, and energy dissipation due to particle-particle and particle-wall collisions, the role of gas-solid interaction and inelastic collisions between the particles are elucidated. It is concluded that the competition between gas-solid interaction and particle-particle interaction determines the pattern formation in high-velocity gas-solid flows: if the gas-solid interaction (under elevated pressure) dominates, most of particle energy obtained by drag from the gas phase is partitioned such that particle potential energy is raised, leading to a uniform flow structure. Otherwise, a heterogeneous pattern exists, which could be induced by both particle-particle collisions and gas-solid interaction. Although both factors could cause the flow instability, the non-linear drag force is demonstrated to be the necessary condition to trigger heterogeneous flow structure formation. As gas velocity increases and goes beyond a critical value, the fluid-particle interaction suppresses particle collisional dissipation, and as a consequence a more homogeneous flow regime is formed

Direct numerical simulation of fluid flow accompanied by coupled mass and heat transfer in dense fluid-particle systems

In this paper we report the extension of an earlier reported DNS method (Deen et al., 2012 and Deen and Kuipers, 2013) based on a novel Immersed Boundary Method (IBM) which incorporates the fluid–solid coupling at the level of the discrete field equations. The extended method is used to study coupled mass and heat transport in dense fluid–particle systems where the coupling arises as a consequence of an exothermal chemical reaction proceeding at the exterior surface of the particles. Following a detailed verification (using an independent numerical technique) and validation (using established empirical correlations) we apply our DNS technique to study coupled mass and heat transfer in a dense fluid–particle system. In addition a comparison is made with results obtained from a simple one-dimensional (1D) heterogeneous reactor model which uses empirical closures for the fluid–particle mass and heat transfer coefficients. The main features of the complex transient temperature profiles obtained from our DNS agree quite well with the corresponding profiles obtained from the 1D heterogeneous reactor model

Computational fluid dynamics applied to chemical reaction engineering

In this paper a brief review will be presented on the application of Computational Fluid Dynamics (CFD) to the field of Chemical Reaction Engineering (CRE) with emphasis on multiphase flow due to its practical importance. The theoretical framework will be briefly discussed together with available computational strategies for dispersed multiphase flows. Finally some typical results will be presented for one particular class of mutiphase flow

Characterizing solids mixing in DEM simulations

In the production and processing of granular matter, solids mixing plays an important role. Granular materials such as sand, polymeric particles and fertilizers are processed in different apparatus such as fluidized beds, rotary kilns and spouted beds. In the operation of these apparatus mixing often plays an important role, as it helps to prevent formation of hot-spots, off-spec products and undesired agglomerates. DEM can be used to simulate these granular systems and provide insight in mixing phenomena. Several methods to analyse and characterize mixing on basis of DEM data have been proposed in the past, but there is no general consensus on what method to use. In this paper we discuss various methods that are able to give quantitative information on the solids mixing state in granular systems based on DEM simulations. We apply the different methods to full 3D DEM simulations of a fluidized bed at different operating pressures. The following analysis methods will be investigated: average height method, Lacey index, nearest neighbours method, partner distance method and the sphere radius method. It is found that some of these methods are grid dependent, are not reproducible, are sensitive to macroscopic flow patters and/or are only able to calculate overall mixing indices, rather than indices for each direction. We compare some methods described in literature and in addition propose two new methods, which do not suffer from the disadvantages mentioned above. We applied each of these aforementioned methods to full 3D discrete particle simulations (DPM) with 280·103 particles and we performed simulations for seven different operating pressures. We found that, mixing improves with operating pressure caused by increased porosity and the increased granular temperature of the particulate phase

Discrete particle simulations of high pressure fluidization

Low density polyethylene and polypropylene are produced at large scale via the Unipol process. In this process catalyst particles are fluidized with monomer gas which reacts with the catalyst particles to form polymeric particles up to a size of 1 mm. The process is typically operated at pressures of 20 to 25 bar. Pressure impacts the hydrodynamics of the fluidized bed as it influences the bubble behaviour, particle mixing and heat transfer characteristics. Despite decades of research on fluid beds these effects are not completely understood. In order to gain more insight in the effects of operating pressure on the fluidization behaviour we have performed full 3D discrete particle simulations. We use a state-of-the art discrete particle model (DPM) to simulate fluidization behaviour at different pressures. In our model the gas phase is described by the volume-averaged Navier-Stokes equations, whereas the particles are described by the Newtonian equations of motion. The DPM accurately accounts for the gas-particle interaction, which is necessary for capturing the pressure effect. The simulation results were analysed with spectral analysis of the pressure drop fluctuations and analysis of the porosity field. In order to study the bubble behaviour, a sophisticated bubble detection algorithm was developed. From this algorithm, gas bubble characteristics, such as bubble velocity and bubble size are obtained. The simulation results show increasing emulsion porosity and decreasing bubble porosity with increasing pressure. In other words, the bubble-emulsion structure becomes less distinct. The determined bubble velocity is very well in accordance with empirical correlations for low pressures, and decreases at elevated pressures

Computing interface curvature from volume fractions: a hybrid approach

The Volume of Fluid method is extensively used for the multiphase flows simulations in which the interface between two fluids is represented by a discrete and abruptly-varying volume fractions field. The Heaviside nature of the volume fractions field presents an immense challenge for the accurate computation of the interface curvature and induces the spurious velocities in the flows with surface-tension effects. A 3D hybrid approach is presented combining the Convolution and Generalized Height Function method for the curvature computation. The volumetric surface tension forces are computed using the balanced-force continuum surface force model. It provides a high degree of robustness at lower grid resolutions with first-order convergence and high accuracy at higher grid resolutions with second-order convergence. The present method is validated for several test cases including a stationary droplet, an oscillating droplet and the buoyant rise of gas bubbles over a wide range of Eötvös (Eo) and Morton (Mo) numbers. Our computational results show an excellent agreement with analytical/experimental results with desired convergence behavior

Direct numerical simulation of fluid flow and dependently coupled heat and mass transfer in fluid-particle systems

\u3cp\u3eIn this paper, an efficient ghost-cell based immersed boundary method (IBM) is used to perform direct numerical simulation (DNS) of reactive fluid-particle systems. With an exothermic first order reaction proceeding at the exterior particle surface, the solid temperature rises and consequently increases the reaction rate via an Arrhenius temperature dependence. In other words, the heat and mass transport is dependently coupled through the particle thermal energy equation and the Arrhenius equation, and they offer dynamic boundary conditions for the fluid phase thermal energy equation and species equation respectively. The fluid-solid coupling is enforced at the exact position of the particle surface by implicit incorporation of the boundary conditions into the discretized momentum, species and thermal energy conservation equations of the fluid phase. Different fluid-particle systems are studied with increasing complexity: a single sphere, three spheres and a dense array consisting of hundreds of randomly generated particles. In these systems the mutual impacts between heat and mass transport processes are investigated.\u3c/p\u3