Numerical Approximation of Optimal Convex and Rotationally Symmetric Shapes for an Eigenvalue Problem arising in Optimal Insulation
Optimization and Control
2022-06-13 v2 Numerical Analysis
Numerical Analysis
Abstract
We are interested in the optimization of convex domains under a PDE constraint. Due to the difficulties of approximating convex domains in , the restriction to rotationally symmetric domains is used to reduce shape optimization problems to a two-dimensional setting. For the optimization of an eigenvalue arising in a problem of optimal insulation, the existence of an optimal domain is proven. An algorithm is proposed that can be applied to general shape optimization problems under the geometric constraints of convexity and rotational symmetry. The approximated optimal domains for the eigenvalue problem in optimal insulation are discussed.
Keywords
Cite
@article{arxiv.2111.03364,
title = {Numerical Approximation of Optimal Convex and Rotationally Symmetric Shapes for an Eigenvalue Problem arising in Optimal Insulation},
author = {Hedwig Keller and Sören Bartels and Gerd Wachsmuth},
journal= {arXiv preprint arXiv:2111.03364},
year = {2022}
}