Algorithmic grid selection in LES

Given the recent progress in LES modeling and numerical schemes the computational grid has now become the single most important factor determining the quality of an LES; and yet the current state-of-the-art is to rely fully on user expertise to build the grid. While this is a workable process for academic problems in relatively simple geometries, it becomes untenable going forward towards more complex flows in complex geometries with multi-physics effects at increasing computational scales. The present work is aimed at developing an algorithmic process for how to select a nearly optimal grid (maximal accuracy at minimal cost) for LES. Two error indicators are used to drive an iterative grid selection process, where the solution from a previous LES run is used to select a more optimal grid for a subsequent run. The resulting method is highly systematic, with minimal dependence on user input, and can be operated both in a free mode that results in unstructured grids and in a constrained mode that results in structured grids. The process is tested on a variety of test cases, including wall-resolved and wall-modeled LES of both canonical flows (channels and boundary layers) and more complex flows (backward-facing step and smooth-body separation) with excellent results in all cases.