Simultaneous Shape and Mesh Quality Optimization using Pre-Shape Calculus

TL;DR

This paper introduces a pre-shape calculus-based method to optimize shapes while simultaneously improving mesh quality, ensuring regularized solutions without increasing computational complexity.

Contribution

It develops a novel regularization approach using pre-shape calculus that maintains shape optimality and enhances mesh quality without additional computational costs.

Findings

Regularized solutions guaranteed to exist.

Method preserves original shape optimality.

Effective in 2D shape optimization problems.

Abstract

Computational meshes arising from shape optimization routines commonly suffer from decrease of mesh quality or even destruction of the mesh. In this work, we provide an approach to regularize general shape optimization problems to increase both shape and volume mesh quality. For this, we employ pre-shape calculus (cf. arXiv:2012.09124). Existence of regularized solutions is guaranteed. Further, consistency of modified pre-shape gradient systems is established. We present pre-shape gradient system modifications, which permit simultaneous shape optimization with mesh quality improvement. Optimal shapes to the original problem are left invariant under regularization. The computational burden of our approach is limited, since additional solution of possibly larger (non-)linear systems for regularized shape gradients is not necessary. We implement and compare pre-shape gradient regularization approaches for a hard to solve 2D problem. As our approach does not depend on the choice of metrics representing shape gradients, we employ and compare several different metrics.