Evaluation of deconvolution modelling applied to numerical combustion - Archive ouverte HAL
Article Dans Une Revue Combustion Theory and Modelling Année : 2018

Evaluation of deconvolution modelling applied to numerical combustion

Résumé

A possible modelling approach in the large eddy simulation (LES) of reactive flows is to deconvolve resolved scalars. Indeed, by inverting the LES filter, scalars such as mass fractions are reconstructed. This information can be used to close budget terms of filtered species balance equations, such as the filtered reaction rate. Being ill-posed in the mathematical sense, the problem is very sensitive to any numerical perturbation. The objective of the present study is to assess the ability of this kind of methodology to capture the chemical structure of premixed flames. For that purpose, three deconvolution methods are tested on a one-dimensional filtered laminar premixed flame configuration: the approximate deconvolution method based on Van Cittert iterative deconvolution, a Taylor decomposition-based method, and the regularised deconvolution method based on the minimisation of a quadratic criterion. These methods are then extended to the reconstruction of subgrid scale profiles. Two methodologies are proposed: the first one relies on subgrid scale interpolation of deconvolved profiles and the second uses parametric functions to describe small scales. Conducted tests analyse the ability of the method to capture the chemical filtered flame structure and front propagation speed. Results show that the deconvolution model should include information about small scales in order to regularise the filter inversion. a priori and a posteriori tests showed that the filtered flame propagation speed and structure cannot be captured if the filter size is too large.
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Dates et versions

hal-01653160 , version 1 (22-04-2020)

Identifiants

Citer

Cédric Mehl, Jérôme Idier, Benoit Fiorina. Evaluation of deconvolution modelling applied to numerical combustion. Combustion Theory and Modelling, 2018, 22 (1), pp.38 - 70. ⟨10.1080/13647830.2017.1358405⟩. ⟨hal-01653160⟩
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