NASA NTRS · 20240006379
A Wall-Distance Method for Turbulence Modeling
Abstract
The distance from a grid point to the closest wall surface, wall distance, is a funda- mental quantity in turbulence modeling. Efficiency of wall-distance calculations has become more critical as the size of computational grids has significantly increased in recent years. This paper reports on an initial implementation of a new search-based wall-distance method that is suitable for general unstructured computational fluid dynamics (CFD) grids and tailored for requirements specific for turbulence modeling. The method represents a two-step approach to calculate the wall distance. In the first step, the wall distance is approximated for each grid point as the minimum distance from this point to a vertex of a triangular face at the wall. The point-to-vertex distance calculation is relatively inexpensive but may lead to a significant error in the wall-distance ap- proximation, especially for grid points near the wall. In the second step, for grid points located within a predefined distance ( threshold ) from the wall, the wall distance is computed as the minimum distance to wall faces. As a result, the wall distance is exact for all grid points within the threshold. This two-step approach reduces the computational cost yet achieves high and controllable accuracy in the evaluation of the wall distance. Algorithmic enhancements are presented to improve efficiency of wall-distance computations. Comprehensive assessment of the new method is reported for large-scale unstructured CFD grids generated for the Fifth AIAA CFD High-Lift Prediction Workshop. The performance of the new wall-distance method compares favorably with performance of two established methods implemented in high-performance CFD codes.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
X. Zhang, B. Diskin, A. Walden, E. J. Nielsen. A Wall-Distance Method for Turbulence Modeling. https://ntrs.nasa.gov/citations/20240006379
Cite the original work for its findings. Save a collection to share your selection of sources.