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In this paper we consider a class of unfitted finite element methods for discretization of partial differential equations on surfaces. In this class of methods known as the Trace Finite Element Method (TraceFEM), restrictions or traces of…

Numerical Analysis · Mathematics 2017-07-06 Maxim A. Olshanskii , Arnold Reusken

We present a novel and comparative analysis of finite element discretizations for a nonlinear Rosenau-Burgers model including a biharmonic term. We analyze both continuous and mixed finite element approaches, providing stability, existence,…

Numerical Analysis · Mathematics 2024-02-15 Ankur , Ram Jiwari , Akil Narayan

The finite element method is a well-established method for the numerical solution of partial differential equations (PDEs), both linear and nonlinear. However, the repeated reassemblage of finite element matrices for nonlinear PDEs is…

Numerical Analysis · Mathematics 2022-09-12 Yannis Voet

The Finite Element Method (FEM) is widely used to solve discrete Partial Differential Equations (PDEs) in engineering and graphics applications. The popularity of FEM led to the development of a large family of variants, most of which…

Numerical Analysis · Computer Science 2022-03-10 Teseo Schneider , Yixin Hu , Xifeng Gao , Jeremie Dumas , Denis Zorin , Daniele Panozzo

In this work we develop and analyze an adaptive finite element method for efficiently solving electrical impedance tomography -- a severely ill-posed nonlinear inverse problem for recovering the conductivity from boundary voltage…

Numerical Analysis · Mathematics 2019-05-16 Bangti Jin , Yifeng Xu , Jun Zou

The phase field model is a widely used mathematical approach for describing crack propagation in continuum damage fractures. In the context of phase field fracture simulations, adaptive finite element methods (AFEM) are often employed to…

Numerical Analysis · Mathematics 2025-05-30 Tian Tian , Chen Chunyu , He Liang , Wei Huayi

We propose a new discretization method for PDEs on moving domains in the setting of unfitted finite element methods, which is provably higher-order accurate in space and time. In the considered setting, the physical domain that evolves…

Numerical Analysis · Mathematics 2022-02-18 Yimin Lou , Christoph Lehrenfeld

The numerical solution of implicit and stiff differential equations by implicit numerical integrators has been largely investigated and there exist many excellent efficient codes available in the scientific community, as Radau5 (based on a…

Numerical Analysis · Mathematics 2025-06-27 Nicola Guglielmi , Ernst Hairer

In this article I present a fast and direct method for solving several types of linear finite difference equations (FDE) with constant coefficients. The method is based on a polynomial form of the translation operator and its inverse, and…

Numerical Analysis · Mathematics 2011-11-03 S. Merino

The finite element method (FEM) is a cornerstone numerical technique for solving partial differential equations (PDEs). Here, we present $\textbf{Qu-FEM}$, a fault-tolerant era quantum algorithm for the finite element method. In contrast to…

Quantum Physics · Physics 2025-10-22 Ahmad M. Alkadri , Tyler D. Kharazi , K. Birgitta Whaley , Kranthi K. Mandadapu

This paper studies adaptive first-order least-squares finite element methods for second-order elliptic partial differential equations in non-divergence form. Unlike the classical finite element method which uses weak formulations of PDEs…

Numerical Analysis · Mathematics 2019-06-28 Weifeng Qiu , Shun Zhang

In this paper, a compact alternating direction implicit (ADI) method has been developed for solving two-dimensional Riesz space fractional diffusion equation. The precision of the discretization method used in spatial directions is twice…

Numerical Analysis · Mathematics 2020-04-21 Sohrab Valizadeh , Alaeddin Malek , Abdollah Borhanifar

Developing efficient numerical algorithms for the solution of high dimensional random Partial Differential Equations (PDEs) has been a challenging task due to the well-known curse of dimensionality. We present a new solution framework for…

Machine Learning · Computer Science 2019-10-17 Mohammad Amin Nabian , Hadi Meidani

The paper is concerned with the adaptive finite element solution of linear elliptic differential equations using equidistributing meshes. A strategy is developed for defining this type of mesh based on residual-based a posteriori error…

Numerical Analysis · Mathematics 2020-04-20 Yinnian He , Weizhang Huang

The adaptive nonconforming Morley finite element method (FEM) approximates a regular solution to the von K\'{a}rm\'{a}n equations with optimal convergence rates for sufficiently fine triangulations and small bulk parameter in the D\"orfler…

Numerical Analysis · Mathematics 2020-11-18 Carsten Carstensen , Neela Nataraj

This paper uses the HCT finite element method and mesh adaptation technology to solve the nonlinear plate bending problem and conducts error analysis on the iterative method, including a priori and a posteriori error estimates. Our…

Numerical Analysis · Mathematics 2025-03-17 Akakpo A. Wilfried , Houédanou K. Wilfrid

In this paper, we define new unfitted finite element methods for numerically approximating the solution of surface partial differential equations using bulk finite elements. The key idea is that the $n$-dimensional hypersurface, $\Gamma…

Numerical Analysis · Mathematics 2014-03-21 Klaus Deckelnick , Charles M. Elliott , Thomas Ranner

Multiscale and multiphysics problems need novel numerical methods in order for them to be solved correctly and predictively. To that end, we develop a wavelet based technique to solve a coupled system of nonlinear partial differential…

Numerical Analysis · Mathematics 2023-03-22 Cale Harnish , Luke Dalessandro , Karel Matous , Daniel Livescu

This paper introduces Finite Elements with Switch Detection (FESD), a numerical discretization method for nonsmooth differential equations. We consider the Filippov convexification of these systems and a transformation into dynamic…

Optimization and Control · Mathematics 2024-02-13 Armin Nurkanović , Mario Sperl , Sebastian Albrecht , Moritz Diehl

This paper proposes Friedrichs learning as a novel deep learning methodology that can learn the weak solutions of PDEs via a minmax formulation, which transforms the PDE problem into a minimax optimization problem to identify weak…

Numerical Analysis · Mathematics 2023-01-03 Fan Chen , Jianguo Huang , Chunmei Wang , Haizhao Yang
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