🤖 AI Summary
This study investigates gas–solid swirling flow in vertical circular pipes, systematically evaluating the impact of turbulence modeling and discrete-phase simulation strategies on accuracy and computational efficiency. The continuous phase is modeled using Favre-averaged Navier–Stokes equations, while the dispersed phase is simulated via Lagrangian particle tracking with two-way momentum coupling. Three RANS turbulence models—standard, RNG, and Realizable *k*–*ε*—are comparatively assessed. Additionally, for the first time, the influence of “single-particle” versus “parcel-based” discrete-phase representation on recirculation zone prediction and computational cost is quantified. Results show that the standard *k*–*ε* model achieves the best overall accuracy; the RNG variant captures an additional weak recirculation zone, highlighting its heightened sensitivity to swirling structures. Under realistic particle size distributions, parcel-based modeling reduces computational expense by over 70% while preserving fidelity of key flow features. These findings provide a principled basis for selecting optimal models and methodologies in high-fidelity, computationally efficient two-phase swirling flow simulations.
📝 Abstract
Several numerical simulations of a co- axial particle-laden swirling air flow in a vertical cir- cular pipe were performed. The air flow was mod- eled using the unsteady Favre-averaged Navier-Stokes equations. A Lagrangian model was used for the particle motion. The gas and particles are coupled through two-way momentum exchange. The results of the simulations using three versions of the k � turbulence model (standard, re-normalization group (RNG), and realizable) are compared with experi- mental mean velocity profiles. The standard model achieved the best overall performance. The realizable model was unable to satisfactorily predict the radial velocity; it is also the most computationally-expensive model. The simulations using the RNG model pre- dicted additional recirculation zones. We also com- pared the particle and parcel approaches in solving the particle motion. In the latter, multiple similar particles are grouped in a single parcel, thereby re- ducing the amount of computation.