Advances on finite element discretization of fluid–structure interaction problems

Abstract We review the main features of an unfitted finite element method for interface and fluid–structure interaction problems based on a distributed Lagrange multiplier in the spirit of the fictitious domain approach. We recall our theoretical findings concerning well-posedness, stability, and convergence of the numerical schemes, and discuss the related computational challenges. In the case of elliptic interface problems, we also present a posteriori error estimates.

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Publication Details

Journal
Arabian Journal of Mathematics
Published
2025-09-30
DOI
https://doi.org/10.1007/s40065-025-00570-8
Primary Topic
Advanced Numerical Methods in Computational Mathematics
Type
article
Field-Weighted Citation Impact
0.00

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article

Advances on finite element discretization of fluid–structure interaction problems

Najwa Alshehri, Fabio Credali, Daniele Boffi, Lucia Gastaldi
Arabian Journal of Mathematics
Advanced Numerical Methods in Computational Mathematics
article

Advances on finite element discretization of fluid–structure interaction problems

Najwa Alshehri, Fabio Credali, Daniele Boffi, Lucia Gastaldi
article en

Abstract

Abstract We review the main features of an unfitted finite element method for interface and fluid–structure interaction problems based on a distributed Lagrange multiplier in the spirit of the fictitious domain approach. We recall our theoretical findings concerning well-posedness, stability, and convergence of the numerical schemes, and discuss the related computational challenges. In the case of elliptic interface problems, we also present a posteriori error estimates.

Arabian Journal of MathematicsVol. 15(1)
University of Pavia (IT), King Abdullah University of Science and Technology (SA), University of Brescia (IT), Jubail Industrial College (SA)
Istituto Nazionale di Alta Matematica "Francesco Severi", King Abdullah University of Science and Technology, Gruppo Nazionale per il Calcolo Scientifico
Openalex Percentile: Top 71%
Advanced Numerical Methods in Computational Mathematics
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