The objective of this paper is to introduce and demonstrate a robust method for multi-constrained topology optimization. The method is derived by combining the topological sensitivity with the classic augmented Lagrangian formulation. The primary advantages of the proposed method are: (1) it rests on well-established augmented Lagrangian formulation for constrained optimization, (2) the augmented topological level-set can be derived systematically for an arbitrary set of loads and constraints, and (3) the level-set can be updated efficiently. The method is illustrated through numerical experiments.
@article{arxiv.2203.15111,
title = {Multi-constrained topology optimization via the topological sensitivity},
author = {Shiguang Deng and Krishnan Suresh},
journal= {arXiv preprint arXiv:2203.15111},
year = {2022}
}