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The scaled boundary finite element method (SBFEM) is a relatively recent boundary element method that allows the approximation of solutions to PDEs without the need of a fundamental solution. A theoretical framework for the convergence…

Numerical Analysis · Mathematics 2021-03-23 Fleurianne Bertrand , Daniele Boffi , Gonzalo G. de Diego

We consider the numerical approximation of single phase flow in porous media by a mixed finite element method with mass lumping. Our work extends previous results of Wheeler and Yotov, who showed that mass lumping together with an…

Numerical Analysis · Mathematics 2018-12-11 Herbert Egger , Bogdan Radu

We consider the isoparametric finite element method (FEM) for the Poisson equation in a smooth domain with the homogeneous Dirichlet boundary condition. Because the boundary is curved, standard triangulated meshes do not exactly fit it.…

Numerical Analysis · Mathematics 2025-03-13 Takahito Kashiwabara

The solution to an optimal power flow (OPF) problem provides a minimum cost operating point for an electric power system. The performance of OPF solution techniques strongly depends on the problem's feasible space. This paper presents an…

Optimization and Control · Mathematics 2016-08-03 Daniel K. Molzahn

We prove optimal error bounds for a second order in time finite element approximation of curve shortening flow in possibly higher codimension. In addition, we introduce a second order in time method for curve diffusion. Both schemes are…

Numerical Analysis · Mathematics 2026-01-29 Klaus Deckelnick , Robert Nürnberg

This work combines the consistency in lower-order differential operators with external approximations of functional spaces to obtain error estimates for finite difference finite volume schemes on unstructured non-uniform meshes. This…

Numerical Analysis · Mathematics 2016-12-02 Qingshan Chen

The theory of mixed finite element methods for solving different types of elliptic partial differential equations in saddle point formulation is well established since many decades. This topic was mostly studied for variational formulations…

Numerical Analysis · Mathematics 2024-03-04 Vitoriano Ruas

A computer-assisted proof is proposed for the Laplacian eigenvalue minimization problems over triangular domains under diameter constraints. The proof utilizes recently developed guaranteed computation methods for both eigenvalues and…

Numerical Analysis · Mathematics 2022-09-30 Ryoki Endo , Xuefeng Liu

Non-orthogonality errors in unstructured Finite Volume methods for simulating incompressible two-phase flows may break the force-balanced discretization. We show that applying the same explicit non-orthogonality correction for all gradient…

Computational Physics · Physics 2024-02-07 Jun Liu , Tobias Tolle , Tomislav Maric

We demonstrate an iterative scheme to approximate the optimal transportation problem with a discrete target measure under certain standard conditions on the cost function. Additionally, we give a finite upper bound on the number of…

Optimization and Control · Mathematics 2012-10-10 Jun Kitagawa

We develop and analyse finite volume methods for the Poisson problem with boundary conditions involving oblique derivatives. We design a generic framework, for finite volume discretisations of such models, in which internal fluxes are not…

Numerical Analysis · Mathematics 2019-08-12 Jerome Droniou , Matej Medla , Karol Mikula

We study a fully discrete finite element method for variable-order time-fractional diffusion equations with a time-dependent variable order. Optimal convergence estimates are proved with the first-order accuracy in time (and second order…

Numerical Analysis · Mathematics 2019-05-15 Xiangcheng Zheng , Fanhai Zeng , Hong Wang

An optimization method used in image-processing (metamorphosis) is found to imply Euler's equations for incompressible flow of an inviscid fluid, without requiring that the Lagrangian particle labels exactly follow the flow lines of the…

Chaotic Dynamics · Physics 2015-05-13 Darryl D. Holm

In this article, the piecewise-linear finite element method (FEM) is applied to approximate the solution of time-fractional diffusion equations on bounded convex domains. Standard energy arguments do not provide satisfactory results for…

Numerical Analysis · Mathematics 2018-11-06 Samir Karaa , Kassem Mustapha , Amiya K. Pani

We analyze the flux conservation property of the finite element method. It is shown that the finite element solution does approximate the flux locally in the optimal order, i.e., the same order as that of the nodal interpolation operator.…

Numerical Analysis · Mathematics 2012-05-10 Shangyou Zhang , Zhimin Zhang , Qingsong Zou

We consider a scalar conservation law with linear and nonlinear flux function on a bounded domain $\Omega\subset{\R}^2$ with Lipschitz boundary $\partial\Omega.$ We discretize the spatial variable with the standard finite element method…

Numerical Analysis · Mathematics 2026-02-20 Christos Pervolianakis

In this paper, the generalized finite element method (GFEM) for solving second order elliptic equations with rough coefficients is studied. New optimal local approximation spaces for GFEMs based on local eigenvalue problems involving a…

Numerical Analysis · Mathematics 2021-12-22 Chupeng Ma , Robert Scheichl , Tim Dodwell

We prove precise rates of convergence for monotone approximation schemes of fractional and nonlocal Hamilton-Jacobi-Bellman (HJB) equations. We consider diffusion corrected difference-quadrature schemes from the literature and new…

Analysis of PDEs · Mathematics 2023-09-04 Indranil Chowdhury , Espen R. Jakobsen

In this paper, we revisit approximation properties of piecewise polynomial spaces, which contain more than ${\cal P}_{r-1}$ but not ${\cal P}_r$. We develop more accurate upper and lower error bounds that are sharper than those used in…

Numerical Analysis · Mathematics 2015-02-17 Hehu Xie , Zhimin Zhang

This paper presents a lower bound for optimizing a finite sum of $n$ functions, where each function is $L$-smooth and the sum is $\mu$-strongly convex. We show that no algorithm can reach an error $\epsilon$ in minimizing all functions from…

Machine Learning · Statistics 2015-10-06 Alekh Agarwal , Leon Bottou
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