Journal
COMPUTERS & FLUIDS
Volume 179, Issue -, Pages 1-14Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compfluid.2018.10.016
Keywords
Particle-laden flows; Finite-size particles; Turbulence; Direct numerical simulations
Funding
- Portuguese Foundation for Science and Technology [SFRH/BD/85501/2012]
- U.S. National Science Foundation (NSF) [CBET-1706130]
- Fundação para a Ciência e a Tecnologia [SFRH/BD/85501/2012] Funding Source: FCT
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During the last decade, many approaches for resolved-particle simulation (RPS) have been developed for numerical studies of finite-size particle-laden turbulent flows. In this paper, three RPS approaches are compared for a particle-laden decaying turbulence case. These methods are, the Volume-of-Fluid Lagrangian method, based on the viscosity penalty method (VoF-Lag); a direct forcing Immersed Boundary Method, based on a regularized delta function approach for the fluid/solid coupling (IBM); and the Bounce Back scheme developed for Lattice Boltzmann method (LBM-BB). The physics and the numerical performances of the methods are analyzed. Modulation of turbulence is observed for all the methods, with a faster decay of turbulent kinetic energy compared to the single-phase case. Lagrangian particle statistics, such as the velocity probability density function and the velocity autocorrelation function, show minor differences among the three methods. However, major differences between the codes are observed in the evolution of the particle kinetic energy. These differences are related to the treatment of the initial condition when the particles are inserted in an initially single-phase turbulence. The averaged particle/fluid slip velocity is also analyzed, showing similar behavior as compared to the results referred in the literature. The computational performances of the different methods differ significantly. The VoF-Lag method appears to be computationally most expensive. Indeed, this method is not adapted to turbulent cases. The IBM and LBM-BB implementations show very good scaling. (C) 2018 Elsevier Ltd. All rights reserved.
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