Assessment of the symmetry-preserving regularization model on complex flows using unstructured grids

Traditionally, turbulence modelling of industrial flows in complex geometries have been solved using RANS models and unstructured meshes based solvers. The lack of precision of RANS models in these situations and the increase of computational power, together with the emergence of new high-efficiency sparse parallel algorithms, have made possible the use of more accurate turbulent models such as Large Eddy Simulation (LES). Recently, relevant improvements on turbulence modelling based on regularization techniques for the convective (non-linear) terms have been developed. They basically alter the convective terms to reduce the production of small scales of motion by means of vortex-stretching and preserving exactly all inviscid invariants. If symmetry and conservation properties of the convective terms are preserved, this yields a novel class of regularizations (i.e. symmetry-preserving regularization models). These models restrain the convective production of small scales in an unconditional stable manner, meaning that the velocity cannot blow up in the energy-norm (enstrophy norm in 2D). Thus, the numerical algorithm used to solve the governing equations must preserve the symmetry and conservation properties too. At this stage, results using symmetry-preserving regularization models at relatively complex geometries and configurations are of extreme importance for further progress.The main objective of the present paper is the assessment of symmetry-preserving regularization models on unstructured meshes. Three different test cases have been studied: the impinging jet flow, the flow past a circular cylinder and a simplified Ahmed car. The properties of the filters and their performance on general unstructured meshes have also been considered. A detailed analysis considering the Gaussian and the Helmholtz differential filters is presented.