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In this paper subgrid models for LES of droplet-laden non-isothermal channel flow are tested and improved for three Reynolds numbers based on friction velocity, Re τ of 150, 395, and 950 with the aim to develop a simulation method for LES of a droplet-laden Ranque-Hilsch vortex tube. A new subgrid model combining the beneficial properties of the dynamic eddyviscosity model and the approximate deconvolution model is proposed. Furthermore, the subgrid model in the droplet equations based on approximate deconvolution is found to perform well also in non-isothermal channel flow. At the highest Reynolds number in the test the dynamic model yields results with a similar accuracy as the approximate deconvolution model.
. (2013). A hybrid stochastic-deconvolution model for LES of particle-laden flow. Physics of Fluids, 25(12), 123302-1/15. DOI: 10.1063/1.4849536 General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. 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. C 2013 AIP Publishing LLC. [http://dx
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