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Related papers: MetaFEM: A Generic FEM Solver By Meta-expressions

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Conventional physics-informed extreme learning machine (PIELM) often faces challenges in solving partial differential equations (PDEs) involving high-frequency and variable-frequency behaviors. To address these challenges, we propose a…

Machine Learning · Computer Science 2025-10-15 Fei Ren , Sifan Wang , Pei-Zhi Zhuang , Hai-Sui Yu , He Yang

Partial differential equations (PDEs) are fundamental to modeling physical systems, yet solving them remains a complex challenge. Traditional numerical solvers rely on expert knowledge to implement and are computationally expensive, while…

Machine Learning · Computer Science 2026-02-24 Shanda Li , Tanya Marwah , Junhong Shen , Weiwei Sun , Andrej Risteski , Yiming Yang , Ameet Talwalkar

In this paper, we propose a new approach -- the Tempered Finite Element Method (TFEM) -- that extends the Finite Element Method (FEM) to classes of meshes that include zero-measure or nearly degenerate elements for which standard FEM…

Numerical Analysis · Mathematics 2024-11-27 Antoine Quiriny , Václav Kučera , Jonathan Lambrechts , Nicolas Moës , Jean-François Remacle

We propose an energy-stable parametric finite element method (ES-PFEM) for simulating solid-state dewetting of thin films in two dimensions via a sharp-interface model, which is governed by surface diffusion and contact line (point)…

Numerical Analysis · Mathematics 2020-06-08 Quan Zhao , Wei Jiang , Weizhu Bao

Multiscale Finite Element Methods (MsFEM) are finite element type approaches dedicated to multiscale problems. They first compute local, oscillatory, problem-dependent basis functions which generate a specific discretization space, and next…

Numerical Analysis · Mathematics 2023-02-08 Rutger A. Biezemans , Claude Le Bris , Frederic Legoll , Alexei Lozinski

The eXtended Finite Element Method (XFEM) is an approach for solving problems with non-smooth solutions. In the XFEM, the approximate solution is locally enriched to capture discontinuities without requiring a mesh which conforms to the…

Numerical Analysis · Mathematics 2013-12-23 Christapher Lang , David Makhija , Alireza Doostan , Kurt Maute

This paper presents a generalised symbolic algorithm for solving systems of linear algebraic equations with multi-diagonal coefficient matrices. The algorithm is given in a pseudocode. A theorem which gives the condition for correctness of…

Symbolic Computation · Computer Science 2026-05-22 Milena Veneva

We introduce the multivariate decomposition finite element method (MDFEM) for solving elliptic PDEs with uniform random diffusion coefficients. We show that the MDFEM can be used to reduce the computational complexity of estimating the…

Numerical Analysis · Mathematics 2021-07-28 Dong T. P. Nguyen , Dirk Nuyens

We propose a reduced space mixed finite element method (MFEM) built on a Skinning Eigenmode subspace and material-aware cubature scheme. Our solver is well-suited for simulating scenes with large material and geometric heterogeneities in…

Graphics · Computer Science 2024-05-24 Ty Trusty , Otman Benchekroun , Eitan Grinspun , Danny M. Kaufman , David I. W. Levin

The use of nonlinear PDEs has led to significant advancements in various fields, such as physics, biology, ecology, and quantum mechanics. However, finding multiple solutions for nonlinear PDEs can be a challenging task, especially when…

Numerical Analysis · Mathematics 2025-04-11 Wenrui Hao , Sun Lee , Young Ju Lee

In this paper, we develop a multiscale finite element method for solving flows in fractured media. Our approach is based on Generalized Multiscale Finite Element Method (GMsFEM), where we represent the fracture effects on a coarse grid via…

Numerical Analysis · Mathematics 2015-02-16 Yalchin Efendiev , Seong Lee , Guanglian Li , Jun Yao , Na Zhang

Computational Fluid Dynamics (CFD) simulations are essential for analyzing and optimizing fluid flows in a wide range of real-world applications. These simulations involve approximating the solutions of the Navier-Stokes differential…

Fracture produces new mesh fragments that introduce additional degrees of freedom in the system dynamics. Existing finite element method (FEM) based solutions suffer from an explosion in computational cost as the system matrix size…

Graphics · Computer Science 2024-08-19 Avirup Mandal , Parag Chaudhuri , Subhasis Chaudhuri

A hybrid computational approach that integrates the finite element method (FEM) with least squares support vector regression (LSSVR) is introduced to solve partial differential equations. The method combines FEM's ability to provide the…

Numerical Analysis · Mathematics 2026-01-01 Maryam Babaei , Peter Rucz , Manfred Kaltenbacher , Stefan Schoder

We revisit the cell-based smoothed finite element method (SFEM) for quadrilateral elements and extend it to arbitrary polygons and polyhedrons in 2D and 3D, respectively. We highlight the similarity between the SFEM and the virtual element…

Numerical Analysis · Mathematics 2014-10-08 Sundararajan Natarajan , Stéphane P. A. Bordas , Ean Tat Ooi

The Finite Element Method (FEM) is a powerful modeling tool for predicting soft robots' behavior, but its computation time can limit practical applications. In this paper, a learning-based approach based on condensation of the FEM model is…

Numerical approximations of partial differential equations (PDEs) are routinely employed to formulate the solution of physics, engineering, and mathematical problems involving functions of several variables, such as the propagation of heat…

We propose a matrix-free finite element (FE) homogenization scheme that is considerably more efficient than generic FE implementations. The efficiency of our scheme follows from a preconditioned well-scaled reformulation allowing for the…

Numerical Analysis · Mathematics 2022-03-08 Martin Ladecký , Richard J. Leute , Ali Falsafi , Ivana Pultarová , Lars Pastewka , Till Junge , Jan Zeman

An exact arithmetic, memory efficient direct solution method for finite element method (FEM) computations is outlined. Unlike conventional black-box or low-rank direct solvers that are opaque to the underlying physical problem, the proposed…

Computational Engineering, Finance, and Science · Computer Science 2020-02-13 Javad Moshfegh , Marinos N. Vouvakis

Accuracy in neural PDE solvers often breaks down not because of limited expressivity, but due to poor optimisation caused by ill-conditioning, especially in multi-fidelity and stiff problems. We study this issue in Physics-Informed Extreme…

Machine Learning · Computer Science 2025-08-11 Siddharth Rout
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