LES and RANS calculations of particle dispersion behind a wall-mounted cubic obstacle. (June 2022)

• Record Type: Journal Article
• Authors: Atzori, Marco; Chibbaro, Sergio; Duwig, Christophe; Brandt, Luca
• Is Part Of: International journal of multiphase flow. Volume 151(2022)
• Publication Date: 2022-06
• Subjects: Computational fluid dynamics -- Particle dispersion -- Stochastic models; Multiphase flow -- Periodicals; Écoulement polyphasique -- Périodiques; Multiphase flow; Periodicals; 620.1064
• DOI: 10.1016/j.ijmultiphaseflow.2022.104037
• Languages: English
• ISSNs: 0301-9322

Abstract

Abstract: In the present paper, we evaluate the performances of three stochastic models for particle dispersion in the case of a three-dimensional turbulent flow. We consider the flow in a channel with a cubic wall-mounted obstacle, and perform large-eddy simulations (LESs) including passive particles injected behind the obstacle, for cases of low and strong inertial effects. We also perform Reynolds-averaged simulations of the same case, using standard turbulence models, and employ the two discrete stochastic models for particle dispersion implemented in the open-source code OpenFOAM and the continuous Lagrangian stochastic model proposed by Minier et al. (2004). The Lagrangian model is consistent with a Probability Density Function (PDF) model of the exact particle equations, and is based on the modelling of the fluid velocity seen by particles. This approach allows a consistent formulation which eliminates the spurious drifts flawing discrete models and to have the drag force in a closed form. The LES results are used as reference data both for the fluid RANS simulations and particle simulations with dispersion models. The present test case allows to evaluate the performance of dispersion models in highly non-homogeneous flow, and it used in this context for the first time. The continuous stochastic model generally shows a better agreement with the LES than the discrete stochastic models, in particular in the case of particles with higher inertia. Highlights: LES and RANS are performed for the turbulent particle-laden flow around a wall-mounted obstacle. A stochastic model for particle dispersion is implemented in the open-source code OpenFOAM. The model is significantly more effective than a rough randomization of turbulence fluctuations.