Direct numerical simulations of anisotropic homogeneous turbulence using parametric forcing

Turbulence modeling using RANS and LES are pragmatic alternatives to direct numerical simulations (DNS) for predicting complex turbulent flows. However, the predictive reliability of these modeling approaches is limited. Arguably, one of the reasons is that detailed data that could be used to inform such models is generally limited to simple canonical flows. The development of reliable generally applicable turbulence models will be facilitated by the accumulation of a rich set of data from a wide variety of complex turbulent flows. We propose to generate such a rich set of data using DNS in simple computational domains in which artificial forcing is applied to introduce turbulence complexity. As a first step in this direction, a family of anisotropic forcing formulations has been developed that introduce both component and scale anisotropy to homogeneous turbulence simulations. The forcing is formulated as a divergence-free anisotropic linear function of the fluctuating velocity that is applied to an anisotropically distributed set of large-scale Fourier modes. The anisotropy is controlled by four parameters that describe the anisotropy of the forcing and of the scales that are forced. Direct numerical simulations of turbulence with a wide range of anisotropies are being performed, and the resulting data is analyzed to characterize the turbulence anisotropy. The use of these data to inform anisotropic LES and RANS models will be discussed.