Improving the quality of meshes for the simulation of semiconductor devices using Lepp-based algorithms

Abstract

Abstract This paper discusses a new post-process algorithm for generating valid Delaunay meshes for the Box-method (finite-volume method) as required in semiconductor device simulation. In such an application, the following requirements must be considered: (i) in critical zones of the device, edges aligned with the flow of the current (anisotropic meshes) are needed; (ii) boundary and interface triangles with obtuse angles opposite to the boundary/interfaces are forbidden; (iii) large obtuse angles in the interior of the device must be destroyed and (iv) interior vertices with high vertex-edge connectivity should be avoided. By starting from a fine Delaunay mesh that satisfies condition (i), the algorithm produces a Delaunay mesh that fully satisfies condition (ii) and satisfies conditions (iii) and (iv) according to input tolerance parameters γ and c, where γ is a maximum angle tolerance value and c is a maximum vertex-edge connectivity tolerance value. Both to destroy any target interior obtuse triangle t and any target high vertex-edge connectivity, a Lepp–Delaunay algorithm is used. The elimination of obtuse angles opposite to the boundary and/or interfaces is done either by longest edge bisection or by the generation of isosceles triangles. The Lepp–Delaunay algorithm allows a natural improvement of the input mesh by inserting a few points in some existing edges of the current triangulation. Examples of the use of the algorithm over Delaunay constrained meshes generated by a normal offsetting approach will be shown. A comparison with an orthogonal refinement method followed by Voronoi point insertion is also included. Copyright © 2003 John Wiley & Sons, Ltd.

Publication
International Journal for Numerical Methods in Engineering
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.