On the use of particle-wall interaction models to predict particle-laden flow in 90-deg bends

Building Simulation(2020)

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摘要
The objective of this work is to evaluate the capability of different combinations of a turbulence model and a Lagrangian particle tracking (LPT) model integrating a particle-wall interaction (PWI) model to predict particle-laden flow in 90-deg bends, as well as the impact of the PWI model on the prediction of the referred flow. The experimental data from Kliafas and Holt (1987) (LDV measurements of a turbulent air-solid two-phase flow in a 90° bend. Experiments in Fluids , 5: 73-85) concerning a vertical to horizontal square-sectioned duct with a hydraulic diameter of 0.1 m that are connected by a 90-deg bend with a curvature ratio of 3.52, served as the benchmark for the aimed analysis. Air with glass spheres of 50 μm diameter flows in the experimental duct system with a Reynolds number of 3.47×10 5 . The airflow was modelled by four different turbulence models: a low Reynolds number k - ε model, the SST k - ω model, the v 2 - f model, and the RSM SSG model. The particle-phase was modelled by a LPT formulation, and the particle-wall interaction was calculated using four different models: Brauer, Grant & Tabakoff, Matsumoto & Saito and Brach & Dunn PWI models. The 3D simulation results of mean streamwise velocities from the sixteen RANS-LPT/PWI combinations were compared qualitatively and quantitatively to experimental and numerical data available in the literature. The four turbulence models produced errors for the gas-phase in the order of 8%. Concerning the particle-phase, the errors produced by all RANS-LPT/PWI combinations were below 4% for bend angles up to 15° and up to 18% for bend angles higher than 30°. The best results for the particle-phase were obtained with the SST k - ω and v 2 - f model combined with the LPT/Brauer or LPT/Brach & Dunn PWI models, which produced errors inferior to 14%.
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关键词
duct bend,airflow,CFD,Eulerian-Lagrangian approach,turbulence model,particle-wall interaction model
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