Approximate Shape Quality Mesh Generation

Abstract

We present two techniques for simplifying the list processing required in standard iterative refinement approaches to shape quality mesh generation. The goal of these techniques is to gain simplicity of programming, efficiency in execution, and robustness of termination. `Shape quality’ for a mesh generation method usually means that, under suitable conditions, a mesh with all angles exceeding a prescribed tolerance is generated. The methods introduced in this paper are truncated versions of such methods. They depend on the shape improvement properties of the terminal-edge LEPP-Delaunay refinement technique; we refer to them as approximate shape quality methods. They are intended for geometry-based preconditioning of coarse initial meshes for subsequent refinement to meet data representation needs. One technique is an algorithm re-organization to avoid maintaining a global list of triangles to be refined. The re-organization uses a recursive triangle processing strategy. Truncating the recursion depth results in an approximate method. Based on this, we argue that the refinement process can be carried out using a static list of the triangles to be refined that can be identified in the initial mesh. Comparisons of approximate to full shape quality meshes are provided.

Publication
Engineering with Computers
Nancy Hitschfeld Kahler
Nancy Hitschfeld Kahler
+Lab founder | Full Professor Universidad de Chile

Full Professor at the Department of Computer Science, University of Chile. Her main research interests include geometric modeling, geometric meshes, and parallel algorithms (GPU computing), focused in computational science, and engineering applications.