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In this work we present an a priori error analysis for solving the unsteady advection equation on cut cell meshes along a straight ramp in two dimensions. The space discretization uses a lowest order upwind-type discontinuous Galerkin…

Numerical Analysis · Mathematics 2024-11-18 Gunnar Birke , Christian Engwer , Jan Giesselmann , Sandra May

We introduce a variational multiscale closure modeling strategy for the numerical stabilization of proper orthogonal decomposition reduced-order models of convection-dominated equations. As a first step, the new model is analyzed and tested…

Numerical Analysis · Mathematics 2015-03-19 Traian iliescu , Zhu Wang

This paper contains two main contributions. First, it provides optimal stability estimates for advection-diffusion equations in a setting in which the velocity field is Sobolev regular in the spatial variable. This estimate is formulated…

Analysis of PDEs · Mathematics 2021-08-24 Víctor Navarro-Fernández , André Schlichting , Christian Seis

We propose a technique for investigating stability properties like positivity and forward invariance of an interval for method-of-lines discretizations, and apply the technique to study positivity preservation for a class of TVD…

Numerical Analysis · Mathematics 2017-02-15 Imre Fekete , David I. Ketcheson , Lajos Lóczi

In this paper we first study the fixed-time stabilizability of discrete-time switched linear control systems. Using a geometric approach, we derive conditions under which such systems can be stabilized within a prescribed number of steps,…

Optimization and Control · Mathematics 2026-04-30 Picchiotti Flavio , Thiago Alves Lima , Girard Antoine

In this paper, the stability of fractional differential equations (FDEs) with unknown parameters is studied. FDEs bring many advantages to model the physical systems in the nature or man-made systems in the industry. Because this…

Systems and Control · Computer Science 2020-08-13 Mehmet Emir Koksal

A novel efficient and high accuracy numerical method for the time-fractional differential equations (TFDEs) is proposed in this work. We show the equivalence between TFDEs and the integer-order extended parametric differential equations…

Numerical Analysis · Mathematics 2025-05-13 Peng Ding , Zhiping Mao

We put forward the use of total-variation-diminishing (or more generally, strong stability preserving) implicit-explicit Runge-Kutta methods for the time integration of the equations of motion associated with the semiconvection problem in…

Numerical Analysis · Mathematics 2012-03-09 Friedrich Kupka , Natalie Happenhofer , Inmaculada Higueras , Othmar Koch

A mixed accuracy framework for Runge--Kutta methods presented in Grant [JSC 2022] and applied to diagonally implicit Runge--Kutta (DIRK) methods can significantly speed up the computation by replacing the implicit solver by less expensive…

In this paper we discuss a new discretization for the Biot equations. The discretization treats the coupled system of deformation and flow directly, as opposed to combining discretizations for the two separate sub-problems. The coupled…

Numerical Analysis · Mathematics 2017-05-19 Jan Martin Nordbotten

In this study, a novel semi-implicit second-order temporal scheme combined with the finite element method for space discretization is proposed to solve the coupled system of infiltration and solute transport in unsaturated porous media. The…

Numerical Analysis · Mathematics 2024-06-11 Nour-eddine Toutlini , Abdelaziz Beljadid , Azzeddine Soulaïmani

In this paper, we consider Maxwell's equations in linear dispersive media described by a single-pole Lorentz model for electronic polarization. We study two classes of commonly used spatial discretizations: finite difference methods (FD)…

Numerical Analysis · Mathematics 2019-06-26 Yan Jiang , Puttha Sakkaplangkul , Vrushali A. Bokil , Yingda Cheng , Fengyan Li

Various bias-correction methods such as EXTRA, gradient tracking methods, and exact diffusion have been proposed recently to solve distributed {\em deterministic} optimization problems. These methods employ constant step-sizes and converge…

Machine Learning · Computer Science 2023-07-19 Kun Yuan , Sulaiman A. Alghunaim , Bicheng Ying , Ali H. Sayed

Irregular sampling intervals and missing values in real-world time series data present challenges for conventional methods that assume consistent intervals and complete data. Neural Ordinary Differential Equations (Neural ODEs) offer an…

Machine Learning · Computer Science 2025-01-28 YongKyung Oh , Dong-Young Lim , Sungil Kim

We propose a nonlinear Discrete Duality Finite Volume scheme to approximate the solutions of drift diffusion equations. The scheme is built to preserve at the discrete level even on severely distorted meshes the energy / energy dissipation…

Analysis of PDEs · Mathematics 2017-05-31 Clément Cancès , Claire Chainais-Hillairet , Stella Krell

This article reports on the confluence of two streams of research, one emanating from the fields of numerical analysis and scientific computation, the other from topology and geometry. In it we consider the numerical discretization of…

Numerical Analysis · Mathematics 2014-01-29 Douglas N. Arnold , Richard S. Falk , Ragnar Winther

Explicit stabilized integrators are an efficient alternative to implicit or semi-implicit methods to avoid the severe timestep restriction faced by standard explicit integrators applied to stiff diffusion problems. In this paper, we provide…

Numerical Analysis · Mathematics 2022-12-14 Assyr Abdulle , Charles-Edouard Bréhier , Gilles Vilmart

A recent paper [J. A. Evans, D. Kamensky, Y. Bazilevs, "Variational multiscale modeling with discretely divergence-free subscales", Computers & Mathematics with Applications, 80 (2020) 2517-2537] introduced a novel stabilized finite element…

Numerical Analysis · Mathematics 2021-12-21 Sajje Lee Calfy , John A. Evans , David Kamensky

The numerical approximation of an inverse problem subject to the convection--diffusion equation when diffusion dominates is studied. We derive Carleman estimates that are on a form suitable for use in numerical analysis and with explicit…

Numerical Analysis · Mathematics 2020-06-25 Erik Burman , Mihai Nechita , Lauri Oksanen

For the ordinary differential equation (ODE) $\dot{x}(t) = f(t,x)$, $x(0) = x_0$, $t\geq 0$, $x\in R^d$, assume $f$ to be at least continuous in $t$ and locally Lipshitz in $x$, and if necessary, several times continuously differentiable in…

Dynamical Systems · Mathematics 2007-05-23 Divakar Viswanath
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