面向STL模型的几何自适应曲面网格生成

Geometry-based Adaptive Surface Mesh Generation for STL Models

采用保特征的模型分解方法将STL模型分割为多个子域,并为每个子域构建参考平面,将一类基于映射思想的前沿推进曲面网格生成算法应用于子域网格生成。在子域上构建G1连续的三角Bernstein-Bézier曲面,利用曲面的方向导矢计算子域的黎曼度量,在黎曼空间生成参数平面网格,以消除映射畸变。考虑曲面曲率和邻近特征计算边界采样点尺寸,利用采样点的Delaunay三角化为背景网格建立几何自适应尺寸场,通过尺寸场光滑化确保不同尺寸网格之间的合理过渡。数值试验表明,算法能针对复杂的STL模型生成高质量的自适应网格。

An STL model is divided into many sub-domains with features preserved at sub-domain boundaries,and then a parametric plane is constructed for each sub-domain,where a mapping based advancing front mesh generation algorithm is applied to generating high quality triangular mesh.In order to remove mapping distortion between the real and parametric spaces,a G1 continuous triangular Bernstein-Bézier surface is reconstructed for each sub-domain to help calculate the Riemannian metrics of surface points.Mesh sizes of boundary sample points are specified by automatic calculations of curvature and proximity features of surface models.And a size field is built on the Delaunay triangulation of sample points.This field is smoothed to prevent unaccepted large gradation between mesh regions with different element size values.Numerical experiments demonstrate that the proposed algorithm can produce high qualified adaptive mesh for complex STL surfaces.