Architecture of Approximate Deconvolution Models of Turbulence
Quality and Reliability of Large-Eddy Simulations
Johan Meyers; Bernard Geurts; Pierre Sagaut
This report presents the mathematical foundation of approximate deconvolution LES models together with the model phenomenology downstream of the theory. This mathematical foundation now begins to be complete for the incompressible Navier–Stokes equations. It is built upon averaging, deconvolving and addressing closure so as to obtain the physically correct energy and helicity balances in the LES model. We show how this is determined and how correct energy balance implies correct prediction of turbulent statistics. Interestingly, the approach is simple and thus gives a road map to develop models for more complex turbulent flows. We illustrate this herein for the case of MHD turbulence.
Deconvolution, Energy cascade, Helicity, MHD
Labovschii, A.; W. Layton; C. Manica; M. Neda; L. Rebholz; Iuliana Stanculescu; and C. Trenchea. (2008). Architecture of Approximate Deconvolution Models of Turbulence. In Johan Meyers; Bernard Geurts; Pierre Sagaut (Eds.), Quality and Reliability of Large-Eddy Simulations .