Robust topology optimization using a posteriori error estimator for the finite element method
arXiv:1712.030175 citationsh-index: 52
AI Analysis
This work addresses the checkerboard instability in topology optimization for structural engineers, offering an incremental improvement over existing filtering methods.
The authors propose modifying the density-based topology optimization cost functional with a posteriori finite element error estimation to prevent checkerboard patterns and improve solution regularity and robustness.
In our work, we consider the classical density-based approach to the topology optimization. We propose to modify the discretized cost functional using a posteriori error estimator for the finite element method. It can be regarded as a new technique to prevent checkerboards. It also provides higher regularity of solutions and robustness of results.