Analysis of model parameters affecting the pressure profile in a circulating fluidized bed

Investigation on influences of loose gas on gas-solid flows in a circulating fluidized bed (CFB) reactor using full-loop numerical simulation

The influences of loose gas on gas-solid flows in a large-scale circulating fluidized bed (CFB) gasification reactor were investigated using full-loop numerical simulation. The two-fluid model was coupled with the QC-energy minimization in multi-scale theory (EMMS) gas-solid drag model to simulate the fluidization in the CFB reactor. Effects of the loose gas flow rate, Q, on the solid mass circulation rate and the cyclone separation efficiency were analyzed. The study found different effects depending on Q: First, the particles in the loop seal and the standpipe tended to become more densely packed with decreasing loose gas flow rate, leading to the reduction in the overall circulation rate. The minimum Q that can affect the solid mass circulation rate is about 2.5% of the fluidized gas flow rate. Second, the sealing gas capability of the particles is enhanced as the loose gas flow rate decreases, which reduces the gas leakage into the cyclones and improves their separation efficiency. The best loose gas flow rates are equal to 2.5% of the fluidized gas flow rate at the various supply positions. In addition, the cyclone separation efficiency is correlated with the gas leakage to predict the separation efficiency during industrial operation.

Numerical Investigation on Proppant–Water Mixture Transport in Slot under High Reynolds Number Conditions

Water hydraulic fracturing involves pumping low viscosity fluid and proppant mixture into the artificial fracture under a high pumping rate. In that high Reynolds number conditions (HRNCs, Re > 2000), the turbulence effect is one of the key factors affecting proppant transportation and placement. In this paper, a Eulerian multiphase model was used to simulate the proppant particle transport in a parallel slot under HRNCs. Turbulence effects in high pumping rates and frictional stress among the proppant particles were taken into consideration, and the Johnson-Jackson wall boundary conditions were used to describe the particle-wall interaction. The numerical simulation result was validated with laboratory-scale slot experiment results. The simulation results demonstrate that the pattern of the proppant bank is significantly affected by the vortex near the wellbore, and the whole proppant transport process can be divided into four stages under HRNCs. Furthermore, the proppant placement structure and the equilibrium height of proppant dune under HRNCs are comprehensively discussed by a parametrical study, including injection position, velocity, proppant density, concentration, and diameter. As the injection position changes from the lower one to the top one, the unpropped area near the entrance decrease by 7.1 times, and the equilibrium height for the primary dune increase by 5.3%. As the velocity of the slurry jet increases from 2 m/s to 5 m/s (Re = 2000–5000), the vortex becomes stronger, so the non-propped area near the inlet increase by 5.3 times, and the equilibrium height decrease by 5.2%. The change of proppant properties does not significantly change the vortex; however, the equilibrium height is affected by the high-speed flush. Thus, the conventional equilibrium height prediction correlation is not suitable for the HRNCs. Therefore, a modified bi-power law prediction correlation was proposed based on the simulation data, which can be used to accurately predict the equilibrium height of the proppant bank under HRNCs (mean deviation = 3.8%).

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.

Two-fluid Modeling of Geldart A Particles in Gas-solid Bubbling Fluidized Bed: Assessment of Drag Models and Solid Viscosity Correlations

In this work the influences of solid viscosity and the way to scale-down traditional drag models on the predicted hydrodynamics of Geldart A particles in a lab-scale gas-solid bubbling fluidized bed are investigated. To evaluate the effects of drag models, the modified Gibilaro et al. drag model (constant correction factor) and the EMMS drag model (non-constant correction factor) are tested. And the influences of solid viscosity are assessed by considering the empirical model proposed by Gidaspow et al. (1997, Turbulence, Viscosity and Numerical Simulation of FCC Particles in CFB. Fluidization and Fluid-particle Systems, AIChE Annual Meeting, Los Angeles, 58–62) and the models based on kinetic theory of granular flow (KTGF) with or without frictional stress. The resulting hydrodynamics by incorporating the different combinations of the drag model and solid viscosity model into two-fluid model (TFM) simulations are compared with the experimental data of Zhu et al. (2008, Detailed Measurements of Flow Structure inside a Dense Gas-Solids Fluidized Bed.”Powder Technological180:339–349). The simulation results show that the predicted hydrodynamics closely depends on the setting of solid viscosity. When solid viscosity is calculated from the empirical model of Gidaspow et al., both drag models can reasonably predict the radial solid concentration profiles and particle velocity profiles. When the KTGF viscosity model without frictional stress is adopted, the EMMS drag model significantly over-estimates the bed expansion, whereas the modified Gibilaro et al. drag model can still give acceptable radial solid concentration profiles but over-estimate particle upwards and downwards velocity. When KTGF viscosity model with frictional stress is chosen, both drag models predict the occurrence of slugging. At this time, the particle velocity profiles predicted by EMMS drag model are still in well agreement with the experimental data, but the bed expansion is under-estimated.