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Title: A hybrid stochastic-deconvolution model for large-eddy simulation of particle-laden flow

We develop a hybrid model for large-eddy simulation of particle-laden turbulent flow, which is a combination of the approximate deconvolution model for the resolved scales and a stochastic model for the sub-grid scales. The stochastic model incorporates a priori results of direct numerical simulation of turbulent channel flow, which showed that the parameters in the stochastic model are quite independent of Reynolds and Stokes number. In order to correctly predict the flux of particles towards the walls an extra term should be included in the stochastic model, which corresponds to the term related to the well-mixed condition in Langevin models for particle dispersion in inhomogeneous turbulent flow. The model predictions are compared with results of direct numerical simulation of channel flow at a frictional Reynolds number of 950. The inclusion of the stochastic forcing is shown to yield a significant improvement over the approximate deconvolution model for the particles alone when combined with a Stokes dependent weight-factor for the well-mixed term.
Authors:
 [1] ;  [1] ;  [2] ; ;  [3] ;  [4] ;  [5] ;  [2]
  1. Department of Mechanical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven (Netherlands)
  2. (Netherlands)
  3. Department of Applied Physics, Eindhoven University of Technology, 5600 MB Eindhoven (Netherlands)
  4. Institute of Fluid-Flow Machinery, Polish Academy of Sciences, Gdansk (Poland)
  5. Faculty EEMCS, University of Twente, 7500 AE Enschede (Netherlands)
Publication Date:
OSTI Identifier:
22257161
Resource Type:
Journal Article
Resource Relation:
Journal Name: Physics of Fluids (1994); Journal Volume: 25; Journal Issue: 12; Other Information: (c) 2013 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; APPROXIMATIONS; DISPERSIONS; GRIDS; HYBRIDIZATION; LARGE-EDDY SIMULATION; PARTICLES; REYNOLDS NUMBER; STOCHASTIC PROCESSES; STOKES NUMBER; TURBULENT FLOW