Gas-flow distribution in bubbling fluidized beds: CFD-based analysis and impact of operating conditions

© 2017 Elsevier B.V. Gas-flow distribution plays a critical role in the performance of fluidized beds because it directly affects gas residence-time and solids mixing. However, measuring it accurately in the harsh conditions of larger reactors is not possible. Therefore, this study is focused on the development of a rigorous computational framework for quantifying gas-flow distribution during fluidization. To this end, fine-grid simulations are conducted for the bubbling fluidization of two distinct Geldart B particles - 1.15 mm LLDPE and 0.50 mm glass particles, at superficial gas velocities U/Umf = 2 and 3 in a 50 cm diameter bed. The two-fluid model (TFM) is employed to describe the solids motion efficiently and in-house developed tool MS3DATA (Multiphase-flow Statistics using 3D Detection and Tracking Algorithm) to compute detailed bubble statistics. The overall gas flow is divided into three phases: (a) dense flow in areas relatively rich is solids concentration (b) “visible” bubble flow associated with rising bubbles and (c) throughflow accounting for the gas flow which mostly bypasses through bubbles. It is found that conditions within the dense-phase depend largely on the particle properties while bubbling dynamics are significantly affected by superficial gas velocity. Calculations show that the throughflow increases in areas frequented by bubbles because the voidage distribution around bubbles increases the local dense-phase permeability. Throughflow may account for up to 40% of the overall gas flow, especially in the fluidization of large particles. This is not desirable because its residence-time is almost 2 × shorter (as compared to the dense flow) and contributes minimally to solids mixing. Finally, it is shown that in comparison to lab-scales, larger beds exhibit more homogeneous gas mixing. Insights from this study and the methodology developed will be useful in investigating gas flow distribution in complex fuel conversion systems

Comprehensive multivariate sensitivity analysis of CFD-DEM simulations: Critical model parameters and their impact on fluidization hydrodynamics

© 2018 Elsevier B.V. The development of CFD-DEM is critical for investigating particle phenomena and their coupling with reactor transport. However, there continues to be considerable uncertainty in the selection of model parameters because of limitations in: (a) experimental measurements of multi-particle interactions, and (b) computational resources which have restricted most numerical studies to 2D simulations, in very small-scale systems (<50k particles) and/or to local sensitivity analysis. The focus of this study is to identify critical model parameters in 3D CFD-DEM simulations of fluidized beds through multivariate sensitivity analysis and quantify their impact on hydrodynamics. Towards this end, thirteen model parameters are considered and the sampling design matrix is constructed using the Morris-One-At-a-Time (MOAT) screening method. 3D CFD-DEM simulations with almost 170,000 glass bead particles (0.4 mm diameter) are conducted in a small rectangular pulsating fluidized bed, selected because of its repeatable bubbling patterns. Detailed bubble and particle dynamics data from 250+ simulations show that: (a) choosing exceedingly low normal spring stiffness has strong implications on particle velocities; (b) the impact of all contact dissipation parameters (normal restitution, friction and tangential damping) is tightly coupled and sensitivity to any one hinges on the choices of others; and (c) the stability of bubble patterns is contingent on their choices and almost-ideal as well as extremely dissipative systems exhibit no patterns. In addition, by investigating particle dynamics inside and around bubbles, we derive a working expression for the optimal choice of spring stiffness. Overall, this first-of-its-kind analysis provides important guidelines for CFD-DEM model parameter selection and the statistical framework developed here provides a robust strategy for the fundamental investigation of other particle-scale phenomena and simulation-based reactor design and optimization. CFD-DEM, gas-solid fluidization, pulsating reactor, multivariate sensitivity, linear spring-dashpot model, spring stiffnes