An adaptive local deconvolution method for implicit LES

By Stefan Hickel, Nikolaus A. Adams, J. Andrzej Domaradzki. Journal of Computational Physics, 2005

295 citations recorded by the source corpus.

The adaptive local deconvolution method (ALDM) is proposed as a new nonlinear discretization scheme designed for implicit large-eddy simulation (ILES) of turbulent flows. In ILES the truncation error of the discretization of the convective terms functions as a subgrid-scale model. Therefore, the model is implicitly contained within the discretization, and an explicit computation of model terms becomes unnecessary. The discretization is based on a solution-adaptive deconvolution operator which allows to control the truncation error. Deconvolution parameters are determined by an analysis of the spectral numerical viscosity. An automatic optimization based on an evolutionary algorithm is employed to obtain a set of parameters which results in an optimum spectral match for the numerical viscosity with theoretical predictions for isotropic turbulence. Simulations of large-scale forced and decaying three-dimensional homogeneous isotropic turbulence show an excellent agreement with theory and experimental data and demonstrate the good performance of the implicit model. As an example for transitional flows, instability and breakdown of the three-dimensional Taylor-Green vortex are considered. The implicit model correctly predicts instability growth and transition to developed turbulence. It is shown that the implicit model performs at least as well as established explicit models.

Subfields: Atmospheric Science, Computational Mechanics

View Paper: https://www.semanticscholar.org/paper/6f2ed9ecb0f484414d475b7814258cb493782e18

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Citations in the corpus

Turbulence and energy budget in a self-preserving round jet: direct evaluation using large eddy simulation (2009, methodology): “A method has also been proposed recently by Hickel, Adams & Domaradzki (2006) to match the numerical viscosity of ILES schemes with theoretical viscosity for isotropic turbulence.”
A family of high-order targeted ENO schemes for compressible-fluid simulations (2016, background): “Extensive studies with DNS and LES can be found in Brachet et al. (1983)Shu et al. (2005)Hickel et al. (2006).”
Artificial Fluid Properties for Large-Eddy Simulation of Compressible Turbulent Mixing (2007, methodology): “Such is the approach of Implicit Large-Eddy Simulation (ILES) [Schumann, 1975, Fureby and Grinstein, 2002, Margolin and Rider, 2002, 2005, Hickel et al., 2006].”
Simulation of transition and turbulence decay in the Taylor–Green vortex (2007, methodology): “The TGV has been used as fundamental prototype for vortex stretching and consequent production of small-scale eddies, to address the basic dynamics of transition to turbulence based on DNS [ 18 ], and more recently to test SGS models [ 19 ].”
On the accuracy of high-order discretizations for underresolved turbulence simulations (2013, unknown): “[22] describe a high order WENO finite volume based adaptive deconvolution approach for LES and Mathew et al.”
Assessment of variational multiscale models for the large eddy simulation of turbulent incompressible flows (2015, methodology): “Finally, we compare the results obtained using VMS models against those obtained using classical LES based on filtering and the dynamic Smagorinsky closure [40], and another implicit LES method, the adaptive local deconvolution presented in [41].”