Numerical techniques for geodesic approximation in Riemannian shape optimization

Fuente: arXiv
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Auteurs principaux: Loayza-Romero, Estefania, Welker, Kathrin
Format: Preprint
Publié: 2025
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author Loayza-Romero, Estefania
Welker, Kathrin
author_facet Loayza-Romero, Estefania
Welker, Kathrin
contents Shape optimization is commonly applied in engineering to optimize shapes with respect to an objective functional relying on PDE solutions. In this paper, we view shape optimization as optimization on Riemannian shape manifolds. We consider so-called outer metrics on the diffeomorphism group to solve PDE-constrained shape optimization problems efficiently. Commonly, the numerical solution of such problems relies on the Riemannian version of the steepest descent method. One key difference between this version and the standard method is that iterates are updated via geodesics or retractions. Due to the lack of explicit expressions for geodesics, for most of the previously proposed metrics, very limited progress has been made in this direction. Leveraging the existence of explicit expressions for the geodesic equations associated to the outer metrics on the diffeomorphism group, we aim to study the viability of using such equations in the context of PDE-constrained shape optimization. However, solving geodesic equations is computationally challenging and often restrictive. Therefore, this paper discusses potential numerical approaches to simplify the numerical burden of using geodesics, making the proposed method computationally competitive with previously established methods.
format Preprint
id arxiv_https___arxiv_org_abs_2504_01564
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Numerical techniques for geodesic approximation in Riemannian shape optimization
Loayza-Romero, Estefania
Welker, Kathrin
Optimization and Control
49Q10, 58D05, 65K05 (Primary) 53C15, 58D17, 53Z30, 53D25 (Secondary)
Shape optimization is commonly applied in engineering to optimize shapes with respect to an objective functional relying on PDE solutions. In this paper, we view shape optimization as optimization on Riemannian shape manifolds. We consider so-called outer metrics on the diffeomorphism group to solve PDE-constrained shape optimization problems efficiently. Commonly, the numerical solution of such problems relies on the Riemannian version of the steepest descent method. One key difference between this version and the standard method is that iterates are updated via geodesics or retractions. Due to the lack of explicit expressions for geodesics, for most of the previously proposed metrics, very limited progress has been made in this direction. Leveraging the existence of explicit expressions for the geodesic equations associated to the outer metrics on the diffeomorphism group, we aim to study the viability of using such equations in the context of PDE-constrained shape optimization. However, solving geodesic equations is computationally challenging and often restrictive. Therefore, this paper discusses potential numerical approaches to simplify the numerical burden of using geodesics, making the proposed method computationally competitive with previously established methods.
title Numerical techniques for geodesic approximation in Riemannian shape optimization
topic Optimization and Control
49Q10, 58D05, 65K05 (Primary) 53C15, 58D17, 53Z30, 53D25 (Secondary)
url https://arxiv.org/abs/2504.01564