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We present an efficient solver for massively-parallel direct numerical simulations of incompressible turbulent flows. The method uses a second-order, finite-volume pressure-correction scheme, where the pressure Poisson equation is solved…

Fluid Dynamics · Physics 2019-09-13 Pedro Costa

A finite element methodology for large classes of variational boundary value problems is defined which involves discretizing two linear operators: (1) the differential operator defining the spatial boundary value problem; and (2) a Riesz…

Numerical Analysis · Mathematics 2017-12-08 Brendan Keith , Socratis Petrides , Federico Fuentes , Leszek Demkowicz

A fast implementation of the OPED algorithm, a reconstruction algorithm for Radon data introduced recently, is proposed and tested. The new implementation uses FFT for discrete sine transform and an interpolation step. The convergence of…

Numerical Analysis · Mathematics 2007-05-23 Yuan Xu , Oleg Tischenko

This paper is concerned with error estimates of the fully discrete generalized finite element method (GFEM) with optimal local approximation spaces for solving elliptic problems with heterogeneous coefficients. The local approximation…

Numerical Analysis · Mathematics 2021-10-01 Chupeng Ma , Robert Scheichl

In this paper, a direct finite element method is proposed for solving interface problems on unfitted meshes. This new method treats the two interface conditions as an $H^{\frac12}(\Gamma)\times H^{-\frac12}(\Gamma)$ pair for the mutual…

Numerical Analysis · Mathematics 2025-08-19 Jun Hu , Limin Ma

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

In this paper, we construct a combined multiscale finite element method (MsFEM) using the Local Orthogonal Decomposition (LOD) technique to solve the multiscale problems which may have singularities in some special portions of the…

Numerical Analysis · Mathematics 2022-09-14 Kuokuo Zhang , Weibing Deng , Haijun Wu

In order to learn distributed port-Hamiltonian systems (dPHS) using Gaussian processes (GPs), the partitioned finite element method (PFEM) is combined with the Gp-dPHS method. By following a late lumping approach, the discretization of the…

Analysis of PDEs · Mathematics 2026-05-28 Florian Courteville , Iain Henderson , Denis Matignon , Sylvain Dubreuil

We present a ray-based finite element method (ray-FEM) by learning basis adaptive to the underlying high-frequency Helmholtz equation in smooth media. Based on the geometric optics ansatz of the wave field, we learn local dominant ray…

Numerical Analysis · Mathematics 2016-09-01 Jun Fang , Jianliang Qian , Leonardo Zepeda-Núñez , Hongkai Zhao

In this paper we explain how to use the Fast Fourier Transform (FFT) to solve partial differential equations (PDEs). We start by defining appropriate discrete domains in coordinate and frequency domains. Then describe the main limitation of…

Numerical Analysis · Mathematics 2025-07-31 Daniela Rodriguez-Lara , Ivan Alvarez-Rios , Francisco S. Guzman

In this paper a class of higher order finite element methods for the discretization of surface Stokes equations is studied. These methods are based on an unfitted finite element approach in which standard Taylor-Hood spaces on an underlying…

Numerical Analysis · Mathematics 2019-09-19 Thomas Jankuhn , Arnold Reusken

We consider quadrature formulas of high order in time based on Radau-type, L-stable implicit Runge-Kutta schemes to solve time dependent stiff PDEs. Instead of solving a large nonlinear system of equations, we develop a method that performs…

Numerical Analysis · Mathematics 2016-04-04 Max Duarte , Matthew Emmett

When solving the time-dependent radiative transport equation (RTE), implicit time discretization is often employed for its robustness and stability. This results in a sequence of steady-state RTEs with identical cross-sections but varying…

Numerical Analysis · Mathematics 2026-04-24 Qinchen Song , Lei Zhang , Min Tang

Recently, the deep learning method has been used for solving forward-backward stochastic differential equations (FBSDEs) and parabolic partial differential equations (PDEs). It has good accuracy and performance for high-dimensional…

Numerical Analysis · Mathematics 2020-02-04 Shaolin Ji , Shige Peng , Ying Peng , Xichuan Zhang

This is one of our series papers on multistep schemes for solving forward backward stochastic differential equations (FBSDEs) and related problems. Here we extend (with non-trivial updates) our multistep schemes in [W. Zhao, Y. Fu and T.…

Numerical Analysis · Mathematics 2015-02-12 Kong Tao , Weidong Zhao , Tao Zhou

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…

Efficient exploitation of exascale architectures requires rethinking of the numerical algorithms used in many large-scale applications. These architectures favor algorithms that expose ultra fine-grain parallelism and maximize the ratio of…

We combine the parameterization method for invariant manifolds with the finite element method for elliptic PDEs,to obtain a new computational framework for high order approximation of invariant manifolds attached to unstable equilibrium…

Dynamical Systems · Mathematics 2022-03-08 Jorge Gonzalez , J. D Mireles-James , Necibe Tuncer

In this paper, we present a new polygonal finite element method, called the Zipped Finite Element Method, for star-shaped polygons. The proposed approach constructs high-order shape functions as linear combinations of standard finite…

Numerical Analysis · Mathematics 2025-11-27 Stefano Berrone , Lorenzo Neva , Moreno Pintore , Gioana Teora , Fabio Vicini

Designing efficient and accurate numerical solvers for high-dimensional partial differential equations (PDEs) remains a challenging and important topic in computational science and engineering, mainly due to the "curse of dimensionality" in…

Numerical Analysis · Mathematics 2025-08-20 Senwei Liang , Haizhao Yang
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