基于特征识别的多尺度构件网格自动生成算法

随着结构力学领域待解决问题复杂程度不断提高，多尺度构件的高质量网格生成对于其数值模拟的计算精度起着至关重要的作用。本文提出一种基于特征识别的网格自动生成技术方法，该方法将多尺度构件的不同量级尺度几何特征识别出来，根据其不同尺度尺寸设置相关区域的网格尺寸值，利用Delaunay三角化算法和前沿推进法生成能够反映不同尺度几何特征的网格单元，再对小尺度区域周围进行加密处理，最后通过几何指数控制函数将不同尺度网格过渡连接起来，形成多尺度构件的整体网格划分模型。通过2个几何模型的测试表明该方法生成的整体网格质量好，不同尺度区域网格过渡合理，自动化程度较高。

Grid Generation Automation Algorithm of Multi-scale Component Structures Based on Feature Recognition

With the increasing complexity of the problems to be solved in the field of structural mechanics, the high-quality mesh generation of multi-scale component structures plays an important role in the computational accuracy of the numerical simulation. This paper proposes a method for grid generation automation based on feature recognition. In this method, the geometric features of different scale of complex multi-scale component structures are identified, the grid size values of related regions are set according to their different scale sizes. The delaunay triangulation algorithm or advancing front technique are used to generate grid elements，which can reflect the geometric characteristics of different scale, and then the surrounding areas of small scale are encrypted. Finally, the meshes of different scales are connected by geometric exponential control function to form the whole meshing model of complex multi-scale component sructures. The test results of two geometric models show that the overall grid quality generated by this method is good, the mesh transition of different scales is reasonable transition, and the automation degree is high.