A novel approach to shape optimisation with Lipschitz domains
arXiv:2103.13857 · doi:10.1051/cocv/2021108
Abstract
This article introduces a novel method for the implementation of shape optimisation with Lipschitz domains. We propose to use the shape derivative to determine deformation fields which represent steepest descent directions of the shape functional in the topology. The idea of our approach is demonstrated for shape optimisation of -dimensional star-shaped domains, which we represent as functions defined on the unit -sphere. In this setting we provide the specific form of the shape derivative and prove the existence of solutions to the underlying shape optimisation problem. Moreover, we show the existence of a direction of steepest descent in the topology. We also note that shape optimisation in this context is closely related to the Laplacian, and to optimal transport, where we highlight the latter in the numerics section. We present several numerical experiments in two dimensions illustrating that our approach seems to be superior over a widely used Hilbert space method in the considered examples, in particular in developing optimised shapes with corners.
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- PDE constrained shape optimisation with first-order and Newton-type methods in the topology
- Homotopy methods for higher order shape optimization: A globalized shape-Newton method and Pareto-front tracing
- Enforcing Mesh Quality Constraints in Shape Optimization with a Gradient Projection Method
- Shape optimization in with geometric constraints: a study in distributed-memory systems