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This article presents and analyzes a $p^{th}$-degree immersed finite element (IFE) method for elliptic interface problems with nonhomogeneous jump conditions. In this method, jump conditions are approximated optimally by basic IFE and…

Numerical Analysis · Mathematics 2020-04-29 Slimane Adjerid , Ivo Babuska , Ruchi Guo , Tao Lin

In this paper, a shallow Ritz-type neural network for solving elliptic equations with delta function singular sources on an interface is developed. There are three novel features in the present work; namely, (i) the delta function…

Numerical Analysis · Mathematics 2023-06-13 Ming-Chih Lai , Che-Chia Chang , Wei-Syuan Lin , Wei-Fan Hu , Te-Sheng Lin

We present a simple algorithm to approximate the viscosity solution of Hamilton-Jacobi (HJ) equations by means of an artificial deep neural network. The algorithm uses a stochastic gradient descent-based method to minimize the least square…

Numerical Analysis · Mathematics 2024-12-31 Carlos Esteve-Yagüe , Richard Tsai , Alex Massucco

A new finite element method (FEM) using meshes that do not necessarily align with the interface is developed for two- and three-dimensional anisotropic elliptic interface problems with nonhomogeneous jump conditions. The degrees of freedom…

Numerical Analysis · Mathematics 2025-05-20 Haifeng Ji , Zhilin Li

Solving complex fluid-structure interaction (FSI) problems, which are described by nonlinear partial differential equations, is crucial in various scientific and engineering applications. Traditional computational fluid dynamics based…

Computational Physics · Physics 2023-03-24 Xiantao Fan , Jian-Xun Wang

We develop a weak adversarial approach to solving obstacle problems using neural networks. By employing (generalised) regularised gap functions and their properties we rewrite the obstacle problem (which is an elliptic variational…

Optimization and Control · Mathematics 2024-11-28 Amal Alphonse , Michael Hintermüller , Alexander Kister , Chin Hang Lun , Clemens Sirotenko

Computational modeling and simulation of fluid-structure interactions constitute a fundamental cornerstone for advancing aerospace engineering endeavors. This paper addresses the notion and implementation of the immersed boundary method for…

Computational Physics · Physics 2025-12-24 Longqing Ge , Qingdong Cai , Yonghao Zhang , Tianbai Xiao

In this study, we present a novel computational framework that integrates the finite volume method with graph neural networks to address the challenges in Physics-Informed Neural Networks(PINNs). Our approach leverages the flexibility of…

Fluid Dynamics · Physics 2024-05-08 Tianyu Li , Yiye Zou , Shufan Zou , Xinghua Chang , Laiping Zhang , Xiaogang Deng

We present two improved randomized neural network methods, namely RNN-Scaling and RNN-Boundary-Processing (RNN-BP) methods, for solving elliptic equations such as the Poisson equation and the biharmonic equation. The RNN-Scaling method…

Numerical Analysis · Mathematics 2024-07-29 Huifang Zhou , Zhiqiang Sheng

New finite element methods are proposed for elliptic interface problems in one and two dimensions. The main motivation is not only to get an accurate solution but also an accurate first order derivative at the interface (from each side).…

Numerical Analysis · Mathematics 2017-03-02 Fangfang Qin , Zhaohui Wang , Zhijie Ma , Zhilin Li

With recent advancements in computer hardware and software platforms, there has been a surge of interest in solving partial differential equations with deep learning-based methods, and the integration with domain decomposition strategies…

Numerical Analysis · Mathematics 2023-05-18 Qi Sun , Xuejun Xu , Haotian Yi

This paper proposes a domain decomposition subspace neural network method for efficiently solving linear and nonlinear partial differential equations. By combining the principles of domain decomposition and subspace neural networks, the…

Numerical Analysis · Mathematics 2025-05-28 Zhenxing Fu , Hongliang Liu , Zhiqiang Sheng , Baixue Xing

We study unique continuation over an interface using a stabilized unfitted finite element method tailored to the conditional stability of the problem. The interface is approximated using an isoparametric transformation of the background…

Numerical Analysis · Mathematics 2024-08-19 Erik Burman , Janosch Preuss

In this work, we focus on the Neumann-Neumann method (NNM), which is one of the most popular non-overlapping domain decomposition methods. Even though the NNM is widely used and proves itself very efficient when applied to discrete problems…

Numerical Analysis · Mathematics 2023-02-28 Bastien Chaudet-Dumas , Martin J. Gander

We propose an unfitted interface penalty Discontinuous Galerkin-Finite Element Method (UIPDG-FEM) for elliptic interface problems. This hybrid method combines the interior penalty discontinuous Galerkin (IPDG) terms near the…

Numerical Analysis · Mathematics 2025-05-27 Juan Han , Haijun Wu , Yuanming Xiao

We solve Poisson's equation using new multigrid algorithms that converge rapidly. The novel feature of the 2D and 3D algorithms are the use of extra diagonal grids in the multigrid hierarchy for a much richer and effective communication…

Numerical Analysis · Mathematics 2025-10-20 A. J. Roberts

A novel Douglas alternating direction implicit (ADI) method is proposed in this work to solve a two-dimensional (2D) heat equation with interfaces. The ADI scheme is a powerful finite difference method for solving parabolic equations, due…

Numerical Analysis · Mathematics 2014-07-01 Shan Zhao

Let $\Gamma$ be a smooth curve inside a two-dimensional rectangular region $\Omega$. In this paper, we consider the Poisson interface problem $-\nabla^2 u=f$ in $\Omega\setminus \Gamma$ with Dirichlet boundary condition such that $f$ is…

Numerical Analysis · Mathematics 2021-04-19 Qiwei Feng , Bin Han , Peter Minev

This article presents new immersed finite element (IFE) methods for solving the popular second order elliptic interface problems on structured Cartesian meshes even if the involved interfaces have nontrivial geometries. These IFE methods…

Numerical Analysis · Mathematics 2018-10-29 Tao Lin , Yanping Lin , Xu Zhang

We present a novel deep learning approach to approximate the solution of large, sparse, symmetric, positive-definite linear systems of equations. These systems arise from many problems in applied science, e.g., in numerical methods for…

Machine Learning · Computer Science 2022-10-04 Ayano Kaneda , Osman Akar , Jingyu Chen , Victoria Kala , David Hyde , Joseph Teran
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