Adaptive approximations of inclusions in a semilinear elliptic problem related to cardiac electrophysiology

Abstract In this work, we investigate the numerical reconstruction of inclusions in a semilinear elliptic equation arising in the mathematical modeling of cardiac ischemia. We propose an adaptive finite-element method for the resulting constrained minimization problem that is relaxed by a phase-field approach. The a posteriori error estimators of the adaptive algorithm consist of three components, i.e., the state variable, the adjoint variable and the complementary relation. Moreover, using tools from adaptive finite-element analysis and nonlinear optimization, we establish the strong convergence for a subsequence of adaptively generated discrete solutions to a solution of the continuous optimality system. Several numerical examples are presented to illustrate the convergence and efficiency of the adaptive algorithm.

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Publication Details

Journal
IMA Journal of Numerical Analysis
Published
2025-06-28
DOI
https://doi.org/10.1093/imanum/draf041
Primary Topic
Numerical methods in engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

Adaptive approximations of inclusions in a semilinear elliptic problem related to cardiac electrophysiology

Fengru Wang, Bangti Jin, Yifeng Xu
IMA Journal of Numerical Analysis
Numerical methods in engineering
article

Adaptive approximations of inclusions in a semilinear elliptic problem related to cardiac electrophysiology

Fengru Wang, Bangti Jin, Yifeng Xu
article en

Abstract

Abstract In this work, we investigate the numerical reconstruction of inclusions in a semilinear elliptic equation arising in the mathematical modeling of cardiac ischemia. We propose an adaptive finite-element method for the resulting constrained minimization problem that is relaxed by a phase-field approach. The a posteriori error estimators of the adaptive algorithm consist of three components, i.e., the state variable, the adjoint variable and the complementary relation. Moreover, using tools from adaptive finite-element analysis and nonlinear optimization, we establish the strong convergence for a subsequence of adaptively generated discrete solutions to a solution of the continuous optimality system. Several numerical examples are presented to illustrate the convergence and efficiency of the adaptive algorithm.

IMA Journal of Numerical Analysis
Chinese University of Hong Kong (HK), Shanghai Normal University (CN)
National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality, Shanghai Normal University, Chinese University of Hong Kong
Openalex Percentile: Top 83%
Numerical methods in engineering
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Adaptive approximations of inclusions in a semilinear elliptic problem related to cardiac electrophysiology — Fengru Wang, Bangti Jin, et al. · IMA Journal of Numerical Analysis (2025) | TGRS Research Map | TGRS