关键词: 笛卡儿网格, 特征恢复, Spalart-Allmaras湍流模型, LU-SGS格式, 网格重排序

Abstract: The difficulty of applied computational fluid dynamics (CFD) is grid generation of complex configurations. Study of quick and robust grid generation methods is therefore urgently needed. Computational grids are generated by the Cartesian grid method in this article and adaptive refinement is used at high curvature positions. Wall boundaries are snapped by the projection method, and the viscous boundary layer grids are obtained through partitioning the prism grids. Feature recovery technique is used for concave and convex surfaces. The flow solver is second order by using the least squares reconstruction technique. Roe scheme is used for inviscid flux and HolmesConnell method is used for viscous flux. SpalartAllmaras one equation turbulence model is used for turbulence computation. Lowerupper symmetric Gauss-Seidel (LU-SGS) scheme is used for implicit time marching. Grids are reordered for stability. The samples demonstrate that this grid generation method is robust and effective, and satisfies the engineering requirements of flow field computation. The method used in this article is suitable for engineering application.

Key words: Cartesian grid, feature recovery, Spalart-Allmaras turbulence model, LU-SGS scheme, grid reorder