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 W1,∞-topology. The idea of our approach is demonstrated for shape optimisation of n-dimensional star-shaped domains, which we represent as functions defined on the unit (n − 1)-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 W1,∞− 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.

Highlights

  • In the present work we are interested in the numerical solution of a certain class of shape optimisation problems min J (Ω), Ω ∈ S, where S denotes the set of admissible shapes to be specified in the respective application

  • We prove the existence of an optimal Lipschitz–continuous descent direction, for which we derive an explicit formula in the case n = 2

  • In this article we introduce a novel method for the implementation of shape optimisation with Lipschitz domains

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Summary

Introduction

In the present work we are interested in the numerical solution of a certain class of shape optimisation problems min J (Ω), Ω ∈ S, where S denotes the set of admissible shapes to be specified in the respective application. A common approach in order to calculate at least local minima of J consists in applying the steepest descent method by using the shape derivative of J. A common approach in order to determine a descent direction V ∗ employs a Hilbert space setting. A steepest descent method for the numerical solution utilising a Hilbert-space framework for PDE constrained shape optimisation is investigated in [22]. W 1,∞ SHAPE OPTIMISATION WITH LIPSCHITZ DOMAINS we recall that an extensive summary of the state of the art in numerical approaches to shape and topology optimisation is given in Chapters 6–9 of [1]

Analysis of a model problem
Reformulation and existence of a minimum
Discretisation
Lipschitz formula
Sinkhorn algorithm
H1 minimising direction
Numerical experiments
Conclusion
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