A stochastic extension of the approximate deconvolution model

Research output: Contribution to conferencePaperpeer-review

Abstract

The approximate deconvolution model (ADM) for large-eddy simulation exploits a range of represented but non-resolved scales as buffer region for emulating the subgrid-scale energy transfer. ADM can be related to Langevin models for turbulence when filter operators are interpreted as stochastic kernel estimators. The objective of this paper is to introduce the concept of the Eulerian formulation of the Langevin model in a consistent form, allowing for stable numerical integration, and to show how this model can be used for a modified way of subfilter-scale estimation. An initial verification of the concept has been performed for the tree-dimensional Taylor-Green vortex.

Original languageEnglish
StatePublished - 2011
Event7th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2011 - Ottawa, Canada
Duration: 28 Jul 201131 Jul 2011

Conference

Conference7th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2011
Country/TerritoryCanada
CityOttawa
Period28/07/1131/07/11

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