CFD study of mixing and segregation in CFB risers: Extension of EMMS drag model to binary gas–solid flow

Numerical Simulation of the Operating Conditions for the Reduction of Iron Ore Powder in a Fluidized Bed Based on the CPFD Method

In this work, the computational particle fluid dynamics (CPFD) method is used to simulate the high-pressure visual fluidized bed experimental equipment independently designed and developed by the experimentation of the fluidized reduction process of iron ore powder. A numerical model for reducing iron ore fines in a three-dimensional fluidized bed is established, and the model is verified by combining numerical simulation and experimental testing. Moreover, the influences of different reducing factors on the reduction effect in the process of the fluidized reduction of iron ore fines are simulated in detail. Via the CPFD simulation of the fluidized reduction of iron ore fines, the optimal reduction pressure is found to be 0.2 MPa, and the optimal reducing gas is found to be H2. Moreover, the optimal gas velocity is 0.6 m/s, and the optimal reduction temperature is 923 K. This conclusion is consistent with the experimental measurements, so the simulation results can be used to verify the reliability of the optimal operating conditions.

Particle-Scale Simulation of Solid Mixing Characteristics of Binary Particles in a Bubbling Fluidized Bed

The behavior of solid mixing dynamic is of profound significance to the heat transfer and reaction efficiencies in energy engineering. In the current study, the solid mixing characteristics of binary particles in the bubbling fluidized bed are further revealed at particle-scale. Specifically, the influences of gas superficial velocity, Sauter mean diameter (SMD) in the system and the range distribution of particle sizes on the performance of mixing index are quantitatively explored using a computational fluid dynamics-discrete element method (CFD-DEM) coupling model. The competition between solid segregation and the mixing of binary particles is deeply analyzed. There is a critical superficial velocity that maximizes the mixing index of the binary mixture in the bubbling fluidized bed. Solid mixing performs more aggressive when below the critical velocity, otherwise solid segregation overtakes mixing when above this critical velocity. Moreover, superficial velocity is a major factor affecting the mixing efficiency in the binary bubbling fluidized bed. Additionally, the mixing behavior is enhanced with the decrease of SMD while it is deteriorated in the binary system with a wide range of particle size distribution. Therefore, it is highly recommended to perform a binary particle system with smaller SMD and closer particle size distribution for the purpose of enhancing the mixing behavior. The significant understanding of mixing characteristics is expected to provide valuable references for the design, operation, and scale-up of binary bubbling fluidized bed.

Multiscale Eulerian CFD of Chemical Processes: A Review

This review covers the scope of multiscale computational fluid dynamics (CFD), laying the framework for studying hydrodynamics with and without chemical reactions in single and multiple phases regarded as continuum fluids. The molecular, coarse-grained particle, and meso-scale dynamics at the individual scale are excluded in this review. Scoping single-scale Eulerian CFD approaches, the necessity of multiscale CFD is highlighted. First, the Eulerian CFD theory, including the governing and turbulence equations, is described for single and multiple phases. The Reynolds-averaged Navier–Stokes (RANS)-based turbulence model such as the standard k-ε equation is briefly presented, which is commonly used for industrial flow conditions. Following the general CFD theories based on the first-principle laws, a multiscale CFD strategy interacting between micro- and macroscale domains is introduced. Next, the applications of single-scale CFD are presented for chemical and biological processes such as gas distributors, combustors, gas storage tanks, bioreactors, fuel cells, random- and structured-packing columns, gas-liquid bubble columns, and gas-solid and gas-liquid-solid fluidized beds. Several multiscale simulations coupled with Eulerian CFD are reported, focusing on the coupling strategy between two scales. Finally, challenges to multiscale CFD simulations are discussed. The need for experimental validation of CFD results is also presented to lay the groundwork for digital twins supported by CFD. This review culminates in conclusions and perspectives of multiscale CFD.

3D CPFD Simulation of Circulating Fluidized Bed Downer and Riser: Comparisons of Flow Structure and Solids Back-Mixing Behavior

The difference of gas-solids flow between a circulating fluidized bed (CFB) downer and riser was compared by computational particle fluid dynamics (CPFD) approach. The comparison was conducted under the same operating conditions. Simulation results demonstrated that the downer showed much more uniform solids holdup and solids velocity distribution compared with the riser. The radial non-uniformity index of the solids holdup in the riser was over 10 times than that in the downer. In addition, small clusters tended to be present in the whole downer, large clusters tended to be present near the wall in riser. It was found that the different cluster behavior is important in determining the different flow behaviors of solids in the downer and riser. While the particle residence time increased evenly along the downward direction in the downer, particles with both shorter and longer residence time were predicted in the whole riser. The nearly vertical cumulative residence time distribution (RTD) curve in the downer further demonstrated that the solids back-mixing in the downer is limited while that in the riser is severe. Solids turbulence in the downer was much weaker compared with the riser, while the large clusters formation near the wall in the riser would hinder solids transportation ability.

Energy-minimization multiscale based mesoscale modeling and applications in gas-fluidized catalytic reactors

Gas-solid fluidization is intrinsically dynamic and manifests mesoscale structures spanning a wide range of length and timescales. When involved with reactions, more complex phenomena emerge and thus pose bigger challenges for modeling. As the mesoscale is critical to understand multiphase reactive flows, which the conventional two-fluid model without mesoscale modeling may be inadequate to resolve even using extremely fine grids, this review attempts to demonstrate that the energy-minimization multiscale (EMMS) model could be a starting point to develop such mesoscale modeling. Then, the EMMS-based mesoscale modeling with emphasis on formulation of drag coefficients for different fluidization regimes, modification of mass transfer coefficient, and other extensions are discussed in an attempt to resolve the emerging challenges. Its applications with examples of development of novel fluid catalytic cracking and methanol-to-olefins processes prove that the mesoscale modeling plays a remarkable role in improving the predictions in hydrodynamic behaviors and overall reaction rate. However, the product content primarily depends on the chemical kinetic model itself, suggesting the necessity of an effective coupling between chemical kinetics and flow characteristics. The mesoscale modeling can be believed to accelerate the traditional experimental-based scale-up process with much lower cost in the future.