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Main Authors: Bachari, Amina El, Rannou, Johann, Yastrebov, Vladislav A., Kerfriden, Pierre, Claus, Susanne
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2506.17830
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author Bachari, Amina El
Rannou, Johann
Yastrebov, Vladislav A.
Kerfriden, Pierre
Claus, Susanne
author_facet Bachari, Amina El
Rannou, Johann
Yastrebov, Vladislav A.
Kerfriden, Pierre
Claus, Susanne
contents In this article, we introduce a finite element method designed for the robust computation of approximate signed distance functions to arbitrary boundaries in two and three dimensions. Our method employs a novel prediction-correction approach, involving first the solution of a linear diffusion-based prediction problem, followed by a nonlinear minimization-based correction problem associated with the Eikonal equation. The prediction step efficiently generates a suitable initial guess, significantly facilitating convergence of the nonlinear correction step. A key strength of our approach is its ability to handle complex interfaces and initial level set functions with arbitrary steep or flat regions, a notable challenge for existing techniques. Through several representative examples, including classical geometries and more complex shapes such as star domains and three-dimensional tori, we demonstrate the accuracy, efficiency, and robustness of the method, validating its broad applicability for reinitializing diverse level set functions.
format Preprint
id arxiv_https___arxiv_org_abs_2506_17830
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A predictor-corrector scheme for approximating signed distances using finite element methods
Bachari, Amina El
Rannou, Johann
Yastrebov, Vladislav A.
Kerfriden, Pierre
Claus, Susanne
Computational Engineering, Finance, and Science
In this article, we introduce a finite element method designed for the robust computation of approximate signed distance functions to arbitrary boundaries in two and three dimensions. Our method employs a novel prediction-correction approach, involving first the solution of a linear diffusion-based prediction problem, followed by a nonlinear minimization-based correction problem associated with the Eikonal equation. The prediction step efficiently generates a suitable initial guess, significantly facilitating convergence of the nonlinear correction step. A key strength of our approach is its ability to handle complex interfaces and initial level set functions with arbitrary steep or flat regions, a notable challenge for existing techniques. Through several representative examples, including classical geometries and more complex shapes such as star domains and three-dimensional tori, we demonstrate the accuracy, efficiency, and robustness of the method, validating its broad applicability for reinitializing diverse level set functions.
title A predictor-corrector scheme for approximating signed distances using finite element methods
topic Computational Engineering, Finance, and Science
url https://arxiv.org/abs/2506.17830