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The so-called matrix-element method (MEM) has long been used successfully as a classification tool in particle physics searches. In the presence of invisible final state particles, the traditional MEM typically assigns probabilities to an…

High Energy Physics - Phenomenology · Physics 2019-08-26 Stefan von Buddenbrock , Olivier Mattelaer , Michael Spannowsky

Three different displacement based finite element formulations over arbitrary polygons are studied in this paper. The formulations considered are: the conventional polygonal finite element method (FEM) with Laplace interpolants, the…

Numerical Analysis · Mathematics 2013-09-06 Sundararajan Natarajan , Ean Tat Ooi , Irene Chiong , Chongmin Song

In this paper, we consider local multiscale model reduction for problems with multiple scales in space and time. We developed our approaches within the framework of the Generalized Multiscale Finite Element Method (GMsFEM) using space-time…

Numerical Analysis · Mathematics 2016-05-26 Eric T. Chung , Yalchin Efendiev , Wing Tat Leung , Shuai Ye

The performance evaluation of a potentially unstable slope involves two key components: the initiation of the slope failure and the post-failure runout. The Finite Element Method (FEM) excels at modeling the initiation of instability but…

Geophysics · Physics 2022-06-16 Brent Sordo , Ellen Rathje , Krishna Kumar

Complex processes in perforated domains occur in many real-world applications. These problems are typically characterized by physical processes in domains with multiple scales (see Figure 1 for the illustration of a perforated domain).…

Numerical Analysis · Mathematics 2015-01-16 Eric T. Chung , Yalchin Efendiev , Guanglian Li , Maria Vasilyeva

Neural operators (NOs) struggle with high-contrast multiscale partial differential equations (PDEs), where fine-scale heterogeneities cause large errors. To address this, we use the Generalized Multiscale Finite Element Method (GMsFEM) that…

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

We develop a sparse multiscale operator-adapted wavelet decomposition-based finite element method (FEM) on unstructured polygonal mesh hierarchies obtained via a coarsening procedure. Our approach decouples different resolution levels,…

Computational Physics · Physics 2025-12-19 Furkan Şık , F. L. Teixeira , B. Shanker

Since the seminal work of Idelsohn, O\~nate and Del-Pin (2004), the Particle Finite Element Method (PFEM) has relied on a Delaunay triangulation and the Alpha--Shape (AS) algorithm in the remeshing process. This approach guarantees a good…

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…

We present and analyze a new space-time finite element method for the solution of neural field equations with transmission delays. The numerical treatment of these systems is rare in the literature and currently has several restrictions on…

Numerical Analysis · Mathematics 2019-05-16 M. Polner , J. J. W. van der Vegt , S. A. van Gils

We present a new framework for expressing finite element methods on multiple intersecting meshes: multimesh finite element methods. The framework enables the use of separate meshes to discretize parts of a computational domain that are…

Numerical Analysis · Mathematics 2018-08-28 August Johansson , Benjamin Kehlet , Mats G. Larson , Anders Logg

A nonlinear Helmholtz (NLH) equation with high frequencies and corner singularities is discretized by the linear finite element method (FEM). After deriving some wave-number-explicit stability estimates and the singularity decomposition for…

Numerical Analysis · Mathematics 2024-05-28 Run Jiang , Haijun Wu , Yifeng Xu , Jun Zou

We propose and analyze a general framework for space-time finite element methods that is based on least-squares finite element methods for solving a first-order reformulation of the thick parabolic obstacle problem. Discretizations based on…

Numerical Analysis · Mathematics 2025-03-12 José Joaquín Carvajal , Davood Damircheli , Thomas Führer , Francisco Fuica , Michael Karkulik

The Finite Element Method (FEM) is the gold standard for spatial discretization in numerical simulations for a wide spectrum of real-world engineering problems. Prototypical areas of interest include linear heat transfer and linear…

Numerical Analysis · Mathematics 2022-01-10 Marcelo Forets , Daniel Freire Caporale , Jorge M. Pérez Zerpa

When numerical solution of elliptic and parabolic partial differential equations is required to be highly accurate in space, the discrete problem usually takes the form of large-scale and sparse linear systems. In this work, as an…

Numerical Analysis · Mathematics 2024-07-23 Massimo Frittelli , Ivonne Sgura

In this paper, a peridynamics-based finite element method (Peri-FEM) is proposed for the quasi-static fracture analysis, which is of the consistent computational framework with the classical finite element method (FEM). First, the integral…

Computational Engineering, Finance, and Science · Computer Science 2021-09-24 Fei Han , Zhibin Li

In this paper, we propose a general approach called Generalized Multiscale Finite Element Method (GMsFEM) for performing multiscale simulations for problems without scale separation over a complex input space. As in multiscale finite…

Numerical Analysis · Mathematics 2015-06-12 Yalchin Efendiev , Juan Galvis , Thomas Y. Hou

We describe in this work the numerical treatment of the Filament Based Lamellipodium Model (FBLM). The model itself is a two-phase two-dimensional continuum model, describing the dynamics of two interacting families of locally parallel…

Cell Behavior · Quantitative Biology 2015-05-19 A. Manhart , D. Oelz , C. Schmeiser , N. Sfakianakis

We develop and evaluate a method for learning solution operators to nonlinear problems governed by partial differential equations (PDEs). The approach is based on a finite element discretization and aims at representing the solution…

Machine Learning · Computer Science 2025-07-10 Mats G. Larson , Carl Lundholm , Anna Persson