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This content will become publicly available on August 7, 2026

Title: Exact shape derivatives with unfitted finite element methods
Abstract We present an approach to shape optimization problems that uses an unfitted finite element method (FEM). The domain geometry is represented, and optimized, using a (discrete) level set function and we consider objective functionals that are defined over bulk domains. For a discrete objective functional, defined in the unfitted FEM framework, we show that theexactdiscrete shape derivative essentially matches the shape derivative at the continuous level. In other words, our approach has the benefits of both optimize-then-discretize and discretize-then-optimize approaches. Specifically, we establish the shape Fréchet differentiability of discrete (unfitted) bulk shape functionals using both the perturbation of the identity approach and direct perturbation of the level set representation. The latter approach is especially convenient for optimizing with respect to level set functions. Moreover, our Fréchet differentiability results hold foranypolynomial degree used for the discrete level set representation of the domain. We illustrate our results with some numerical accuracy tests, a simple model (geometric) problem with known exact solution, as well as shape optimization of structural designs.  more » « less
Award ID(s):
2111474
PAR ID:
10642924
Author(s) / Creator(s):
 ;  
Publisher / Repository:
Degruyter-Brill
Date Published:
Journal Name:
Journal of Numerical Mathematics
ISSN:
1570-2820
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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