A novel [[EQUATION]] approach to shape optimisation with Lipschitz domains

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 $W^{1,\infty}-$ 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 $W^{1,\infty}-$ topology. We also note that shape optimisation in this context is closely related to the $\infty-$Laplacian, and to optimal transport, where we highlight the latter in the numerics section. We present several numerical experiments illustrating that our approach seems to be superior over existing Hilbert space methods, in particular in developing optimal shapes with corners.

[1]  Stefan Ulbrich,et al.  Analysis of shape optimization problems for unsteady fluid-structure interaction , 2020, Inverse Problems.

[2]  Martin Siebenborn,et al.  A novel p-harmonic descent approach applied to fluid dynamic shape optimization , 2021, Structural and Multidisciplinary Optimization.

[3]  An optimal transportation problem related to the limits of solutions of local and nonlocal $$p$$p-Laplace-type problems , 2015 .

[4]  A. Henrot,et al.  Shape Variation and Optimization: A Geometrical Analysis , 2018 .

[5]  Enrique Fernández-Cara,et al.  The Differentiability of the Drag with Respect to the Variations of a Lipschitz Domain in a Navier--Stokes Flow , 1997 .

[6]  L. Evans Measure theory and fine properties of functions , 1992 .

[7]  Ralf Hiptmair,et al.  Shape Optimization by Pursuing Diffeomorphisms , 2015, Comput. Methods Appl. Math..

[8]  Stefan Ulbrich,et al.  A Continuous Adjoint Approach to Shape Optimization for Navier Stokes Flow , 2009 .

[9]  Stefan Ulbrich,et al.  Fréchet Differentiability of Unsteady Incompressible Navier-Stokes Flow with Respect to Domain Variations of Low Regularity by Using a General Analytical Framework , 2017, SIAM J. Control. Optim..

[10]  Kevin Sturm,et al.  Two-Dimensional Shape Optimization with Nearly Conformal Transformations , 2017, SIAM J. Sci. Comput..

[11]  Gabriel Peyré,et al.  Computational Optimal Transport , 2018, Found. Trends Mach. Learn..

[12]  Andreas Dedner,et al.  The Distributed and Unified Numerics Environment,Version 2.4 , 2016 .

[13]  Martin Eigel,et al.  Reproducing kernel Hilbert spaces and variable metric algorithms in PDE-constrained shape optimization , 2016, Optim. Methods Softw..

[14]  Charles Dapogny,et al.  Shape and topology optimization , 2020 .

[15]  M. Hinze,et al.  Decoupling of Control and Force Objective in Adjoint-Based Fluid Dynamic Shape Optimization , 2019, AIAA Journal.

[16]  Harald Garcke,et al.  Numerical Approximation of Phase Field Based Shape and Topology Optimization for Fluids , 2014, SIAM J. Sci. Comput..

[17]  J. Simon Differentiation with Respect to the Domain in Boundary Value Problems , 1980 .

[18]  M. Delfour,et al.  Shapes and Geometries: Analysis, Differential Calculus, and Optimization , 1987 .

[19]  Hitoshi Ishii,et al.  Limits of Solutions of p-Laplace Equations as p Goes to Infinity and Related Variational Problems , 2005, SIAM J. Math. Anal..

[20]  Martin Siebenborn,et al.  A Continuous Perspective on Shape Optimization via Domain Transformations , 2021, SIAM J. Sci. Comput..

[21]  Martin Siebenborn,et al.  Algorithmic Aspects of Multigrid Methods for Optimization in Shape Spaces , 2016, SIAM J. Sci. Comput..

[22]  Harald Garcke,et al.  A phase field approach to shape optimization in Navier–Stokes flow with integral state constraints , 2017, Advances in Computational Mathematics.

[23]  A. Chakib,et al.  On a shape derivative formula for a family of star-shaped domains , 2020 .

[24]  Jacques Simon,et al.  Etude de Problème d'Optimal Design , 1975, Optimization Techniques.

[25]  Mohamed Masmoudi,et al.  Computation of high order derivatives in optimal shape design , 1994 .

[26]  M. C. Delfour,et al.  Shapes and Geometries - Metrics, Analysis, Differential Calculus, and Optimization, Second Edition , 2011, Advances in design and control.

[27]  R. Hiptmair,et al.  Comparison of approximate shape gradients , 2014, BIT Numerical Mathematics.

[28]  H. Harbrecht Shape optimization for free boundary problems , 2011 .

[29]  Reinhold Schneider,et al.  On Convergence in Elliptic Shape Optimization , 2007, SIAM J. Control. Optim..

[30]  V. Burenkov Sobolev spaces on domains , 1998 .

[31]  Jean Cea Optimization Techniques Modeling and Optimization in the Service of Man Part 2 , 1975, Lecture Notes in Computer Science.

[32]  J. Zolésio,et al.  Introduction to shape optimization : shape sensitivity analysis , 1992 .

[33]  Qingang Xiong,et al.  Development and Application of Open-Source Software for Problems with Numerical PDEs , 2021, Comput. Math. Appl..

[34]  V. Schulz,et al.  Three-Dimensional Large-Scale Aerodynamic Shape Optimization Based on Shape Calculus , 2013 .

[35]  Patrick E. Farrell,et al.  Higher-Order Moving Mesh Methods for PDE-Constrained Shape Optimization , 2017, SIAM J. Sci. Comput..

[36]  Martin Siebenborn,et al.  PDE Constrained Shape Optimization as Optimization on Shape Manifolds , 2015, GSI.

[37]  Martin Siebenborn,et al.  Efficient PDE Constrained Shape Optimization Based on Steklov-Poincaré-Type Metrics , 2015, SIAM J. Optim..

[38]  Utkarsh Ayachit,et al.  The ParaView Guide: A Parallel Visualization Application , 2015 .

[39]  C. M. Elliott,et al.  Computation of geometric partial differential equations and mean curvature flow , 2005, Acta Numerica.

[40]  Filippo Santambrogio,et al.  Optimal Transport for Applied Mathematicians , 2015 .

[41]  Michael Hinze,et al.  A Variational Discretization Concept in Control Constrained Optimization: The Linear-Quadratic Case , 2005, Comput. Optim. Appl..