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Related papers: A penalized {\phi}-FEM scheme for the Poisson Diri…

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This paper is concerned with mixed finite element method (FEM) for solving the two-dimensional, nonlinear fourth-order active fluid equations. By introducing an auxiliary variable $w=-\Delta u$, the original fourth problem is transformed…

Numerical Analysis · Mathematics 2025-07-30 Nan Zheng , Xu Guo , Wenlong Pei , Wenju Zhao

The presented article contains a 2D mesh generation routine optimized with the Metropolis algorithm. The procedure enables to produce meshes with a prescribed size h of elements. These finite element meshes can serve as standard discrete…

Numerical Analysis · Mathematics 2024-10-21 Ilona Dominika Kosinska

In this paper, we introduce a new approach based on distance fields to exactly impose boundary conditions in physics-informed deep neural networks. The challenges in satisfying Dirichlet boundary conditions in meshfree and particle methods…

Numerical Analysis · Mathematics 2022-02-02 N. Sukumar , Ankit Srivastava

This paper is concerned with approximations and related discretization error estimates for the normal derivatives of solutions of linear elliptic partial differential equations. In order to illustrate the ideas, we consider the Poisson…

Numerical Analysis · Mathematics 2018-04-17 J. Pfefferer , M. Winkler

We present partially penalized immersed finite element methods for solving parabolic interface problems on Cartesian meshes. Typical semi-discrete and fully discrete schemes are discussed. Error estimates in an energy norm are derived.…

Numerical Analysis · Mathematics 2016-11-02 Tao Lin , Qing Yang , Xu Zhang

Finite element approximation of the velocity-pressure formulation of the surfaces Stokes equations is challenging because it is typically not possible to enforce both tangentiality and $H^1$ conformity of the velocity field. Most previous…

Numerical Analysis · Mathematics 2025-11-12 Alan Demlow , Michael Neilan

This work proposes an $r$-adaptive finite element method (FEM) using neural networks (NNs). The method employs the Ritz energy functional as the loss function, currently limiting its applicability to symmetric and coercive problems, such as…

An artificial intelligence-augmented Streamline Upwind/Petrov-Galerkin finite element scheme (AiStab-FEM) is proposed for solving singularly perturbed partial differential equations. In particular, an artificial neural network framework is…

Analysis of PDEs · Mathematics 2022-11-28 Sangeeta Yadav , Sashikumaar Ganesan

Consider the Poisson equation with the Dirichlet boundary condition on a three-dimensional polyhedral domain. For singular solutions from the non-smoothness of the domain boundary, we propose new anisotropic tetrahedral mesh refinement…

Numerical Analysis · Mathematics 2016-12-21 Hengguang Li

In this paper we propose a new finite element method for solving elliptic optimal control problems with pointwise state constraints, including the distributed controls and the Dirichlet or Neumann boundary controls. The main idea is to use…

Numerical Analysis · Mathematics 2023-06-07 Wei Gong , Zhiyu Tan

This paper presents an asymptotically compatible error bound for the finite element method (FEM) applied to a nonlocal diffusion model. The analysis covers two scenarios: meshes with and without shape regularity. For shape-regular meshes,…

Numerical Analysis · Mathematics 2025-06-06 Yanzun Meng , Zuoqiang Shi

In this paper, we present a new framework how a PDE with constraints can be formulated into a sequence of PDEs with no constraints, whose solutions are convergent to the solution of the PDE with constraints. This framework is then used to…

Numerical Analysis · Mathematics 2024-05-28 Jiwei Jia , Young Ju Lee , Ruitong Shan

In this article, we introduce a new partially penalized immersed finite element method (IFEM) for solving elliptic interface problems with multi-domains and triple-junction points. We construct new IFE functions on elements intersected with…

Numerical Analysis · Mathematics 2020-03-04 Yuan Chen , Songming Hou , Xu Zhang

We present the analytical formulation and the finite element solution of a fractional-order nonlocal continuum model of a Euler-Bernoulli beam. Employing consistent definitions for the fractional-order kinematic relations, the governing…

Numerical Analysis · Mathematics 2021-02-11 Sansit Patnaik , Sai Sidhardh , Fabio Semperlotti

This article presents an error analysis of the symmetric linear/bilinear partially penalized immersed finite element (PPIFE) methods for interface problems of Helmholtz equations. Under the assumption that the exact solution possesses a…

Numerical Analysis · Mathematics 2020-06-22 Ruchi Guo , Tao Lin , Yanping Lin , Qiao Zhuang

In this paper, we propose a way to solve partial differential equations (PDEs) by combining machine learning techniques and the finite element method called Phi-FEM. For that, we use the Fourier Neural Operator (FNO), a learning mapping…

Numerical Analysis · Mathematics 2025-03-05 Michel Duprez , Vanessa Lleras , Alexei Lozinski , Vincent Vigon , Killian Vuillemot

The Boundary Element Method (BEM) is implemented using piecewise linear elements to solve the two-dimensional Dirichlet problem for Laplace's equation posed on a disk. A benefit of the BEM as opposed to many other numerical solution…

Numerical Analysis · Mathematics 2024-01-23 Misael M. Morales , Shirley Pomeranz

A posteriori upper and lower bounds are derived for the linear finite element method (FEM) for the Helmholtz equation with large wave number. It is proved rigorously that the standard residual type error estimator seriously underestimates…

Numerical Analysis · Mathematics 2021-10-25 Songyao Duan , Haijun Wu

We consider a new fictitious domain approach of higher order accuracy. To implement Dirichlet conditions we apply the classical Nitsche method combined with a facet-based stabilization (ghost penalty). Both techniques are combined with a…

Numerical Analysis · Mathematics 2017-07-04 Christoph Lehrenfeld

We present a novel approach that integrates unfitted finite element methods and neural networks to approximate partial differential equations on complex geometries. Easy-to-generate background meshes (e.g., a simple Cartesian mesh) that cut…

Numerical Analysis · Mathematics 2025-12-04 Wei Li , Alberto F. Martín , Santiago Badia