A discretize-then-optimize approach to PDE-constrained shape optimization

We consider discretized two-dimensional PDE-constrained shape optimization problems, in which shapes are represented by triangular meshes. Given the connectivity, the space of admissible vertex positions was recently identified to be a smooth manifold, termed the manifold of planar triangular meshes...

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Bibliographic Details
Main Authors: Herzog, Roland (Author) , Loayza Romero, Karen (Author)
Format: Article (Journal)
Language:English
Published: 28 February 2024
In: Control, optimisation and calculus of variations
Year: 2024, Volume: 30, Pages: 1-36
ISSN:1262-3377
DOI:10.1051/cocv/2023071
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1051/cocv/2023071
Verlag, kostenfrei, Volltext: https://www.esaim-cocv.org/articles/cocv/abs/2024/01/cocv210177/cocv210177.html
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Author Notes:Roland Herzog and Estefanía Loayza-Romero
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Summary:We consider discretized two-dimensional PDE-constrained shape optimization problems, in which shapes are represented by triangular meshes. Given the connectivity, the space of admissible vertex positions was recently identified to be a smooth manifold, termed the manifold of planar triangular meshes. The latter can be endowed with a complete Riemannian metric, which allows large mesh deformations without jeopardizing mesh quality; see R. Herzog and E. Loayza-Romero, Math. Comput. <b>92<b/> (2022) 1-50. Nonetheless, the discrete shape optimization problem of finding optimal vertex positions does not, in general, possess a globally optimal solution. To overcome this ill-possedness, we propose to add a mesh quality penalization term to the objective function. This allows us to simultaneously render the shape optimization problem solvable, and keep track of the mesh quality. We prove the existence of a globally optimal solution for the penalized problem and establish first-order necessary optimality conditions independently of the chosen Riemannian metric. Because of the independence of the existence results of the choice of the Riemannian metric, we can numerically study the impact of different Riemannian metrics on the steepest descent method. We compare the Euclidean, elasticity, and a novel complete metric, combined with Euclidean and geodesic retractions to perform the mesh deformation.
Item Description:Gesehen am 24.07.2024
Physical Description:Online Resource
ISSN:1262-3377
DOI:10.1051/cocv/2023071