A self-organizing neural network approach for automatic mesh generation

Abstract

An automatic mesh generator, SOFT (self-organizing finite-element tessellation), based on self-organizing neural networks has been demonstrated. With user-supplied mesh density function and boundary mesh, this mesh generator provides a graded mesh, with asymptotic characteristics quite similar to weighted Dirichlet tessellation and dual Delaunay triangulation. Local mesh restrictions such as fixed boundary and/or internal meshes are easily incorporated in this mesh generator. Although the algorithm is applicable to general n-dimensional meshes, two-dimensional rectangular and triangular meshes are presented for simplicity.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>