Saved in:
Bibliographic Details
Main Authors: Schlegel, Luka, Schulz, Volker, Seifried, Frank T., Würschmidt, Maximilian
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2409.15967
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866908786924453888
author Schlegel, Luka
Schulz, Volker
Seifried, Frank T.
Würschmidt, Maximilian
author_facet Schlegel, Luka
Schulz, Volker
Seifried, Frank T.
Würschmidt, Maximilian
contents We introduce a novel mesh-free and direct method for computing the shape derivative in PDE-constrained shape optimization problems. Our approach is based on a probabilistic representation of the shape derivative and is applicable for second-order semilinear elliptic PDEs with Dirichlet boundary conditions and a general class of target functions. The probabilistic representation derives from an extension of a boundary sensitivity result for diffusion processes due to Costantini, Gobet and El Karoui [14]. Moreover, we present a simulation methodology based on our results that does not necessarily require a mesh of the relevant domain, and provide Taylor tests to verify its numerical accuracy
format Preprint
id arxiv_https___arxiv_org_abs_2409_15967
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Probabilistic Approach to Shape Derivatives
Schlegel, Luka
Schulz, Volker
Seifried, Frank T.
Würschmidt, Maximilian
Optimization and Control
Probability
We introduce a novel mesh-free and direct method for computing the shape derivative in PDE-constrained shape optimization problems. Our approach is based on a probabilistic representation of the shape derivative and is applicable for second-order semilinear elliptic PDEs with Dirichlet boundary conditions and a general class of target functions. The probabilistic representation derives from an extension of a boundary sensitivity result for diffusion processes due to Costantini, Gobet and El Karoui [14]. Moreover, we present a simulation methodology based on our results that does not necessarily require a mesh of the relevant domain, and provide Taylor tests to verify its numerical accuracy
title A Probabilistic Approach to Shape Derivatives
topic Optimization and Control
Probability
url https://arxiv.org/abs/2409.15967