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We propose and study a temporal, and spatio-temporal discretisation of the 2D stochastic Navier--Stokes equations in bounded domains supplemented with no-slip boundary conditions. Considering additive noise, we base its construction on the…

Numerical Analysis · Mathematics 2022-03-23 Dominic Breit , Andreas Prohl

In this paper we present a new Eulerian finite element method for the discretization of scalar partial differential equations on evolving surfaces. In this method we use the restriction of standard space-time finite element spaces on a…

Numerical Analysis · Mathematics 2022-12-26 Hauke Sass , Arnold Reusken

We present DeepFDM, a differentiable finite-difference framework for learning spatially varying coefficients in time-dependent partial differential equations (PDEs). By embedding a classical forward-Euler discretization into a convolutional…

Numerical Analysis · Mathematics 2025-07-30 Patrick Chatain , Michael Rizvi-Martel , Guillaume Rabusseau , Adam Oberman

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

In this paper, we introduce a novel category of central compact schemes inspired by existing cell-node and cell-centered compact finite difference schemes, that offer a superior spectral resolution for solving the dispersive wave equation.…

Numerical Analysis · Mathematics 2024-05-03 Lavanya V Salian , Samala Rathan , Debojyoti Ghosh

This work continues a line of works on developing partially explicit methods for multiscale problems. In our previous works, we have considered linear multiscale problems, where the spatial heterogeneities are at subgrid level and are not…

Numerical Analysis · Mathematics 2021-08-31 Eric T. Chung , Yalchin Efendiev , Wing Tat Leung , Wenyuan Li

Methods for solving PDEs using neural networks have recently become a very important topic. We provide an a priori error analysis for such methods which is based on the $\mathcal{K}_1(\mathbb{D})$-norm of the solution. We show that the…

Numerical Analysis · Mathematics 2022-07-15 Qingguo Hong , Jonathan W. Siegel , Jinchao Xu

Optimization with time-dependent partial differential equations (PDEs) as constraints {appears} in many science and engineering applications. The associated first-order necessary optimality system consists of one forward and one backward…

Numerical Analysis · Mathematics 2017-09-28 Jun Liu , Zhu Wang

Time-dependent Partial Differential Equations with given initial conditions are considered in this paper. New differentiation techniques of the unknown solution with respect to time variable are proposed. It is shown that the proposed…

Numerical Analysis · Mathematics 2022-10-24 Marat S. Mukhametzhanov

Immersed boundary methods have attracted substantial interest in the last decades due to their potential for computations involving complex geometries. Often these cannot be efficiently discretized using boundary-fitted finite elements.…

Computational Engineering, Finance, and Science · Computer Science 2026-01-13 Tim Bürchner , Lars Radtke , Philipp Kopp , Stefan Kollmannsberger , Ernst Rank , Alexander Düster

This work focuses on the preconditioning and DC stabilization of the time domain electric field integral equation discretized in time with the convolution quadrature method. The standard formulation of the equation suffers from severe…

Numerical Analysis · Mathematics 2023-05-16 Pierrick Cordel , Alexandre Dély , Adrien Merlini , Francesco P. Andriull

Partial differential equations (PDE) often involve parameters, such as viscosity or density. An analysis of the PDE may involve considering a large range of parameter values, as occurs in uncertainty quantification, control and…

Numerical Analysis · Mathematics 2017-09-28 Max Gunzburger , Nan Jiang , Michael Schneier

Time fractional advection-dispersion equations arise as generalizations of classical integer order advection-dispersion equations and are increasingly used to model fluid flow problems through porous media. In this paper we develop an…

Numerical Analysis · Mathematics 2019-05-16 Carlos E. Mejía , Alejandro Piedrahita

We present and analyze in a unified setting two schemes for the numerical discretization of a Darcy-Forchheimer fluid flow model coupled with an advection-diffusion equation modeling the temperature distribution in the fluid. The first…

Numerical Analysis · Mathematics 2026-02-11 Stefano Bonetti , Michele Botti , Paola F. Antonietti

In this paper we introduce a procedure for identifying optimal methods in parametric families of numerical schemes for initial value problems in partial differential equations. The procedure maximizes accuracy by adaptively computing…

Numerical Analysis · Mathematics 2021-08-10 Gianluca Frasca-Caccia , Pranav Singh

In this work, we consider alternative discretizations for PDEs which use expansions involving integral operators to approximate spatial derivatives. These constructions use explicit information within the integral terms, but treat boundary…

Computational Physics · Physics 2024-11-12 Andrew J. Christlieb , Pierson T. Guthrey , William A. Sands , Mathialakan Thavappiragasm

In this paper, a reduced-order model (ROM) based on the proper orthogonal decomposition and the discrete empirical interpolation method is proposed for efficiently simulating time-fractional partial differential equations (TFPDEs). Both…

Numerical Analysis · Mathematics 2024-02-07 Hongfei Fu , Hong Wang , Zhu Wang

In this paper, we propose a new second-order fast finite difference scheme in time for solving the Tempered Time Fractional Advection-Dispersion Equation. Under the assumption that the solution is nonsmooth at the initial time, we…

Numerical Analysis · Mathematics 2025-12-22 Liangcai Huang , Shujuan Lü

This chapter reviews and compares discontinuous Galerkin time-stepping methods for the numerical approximation of second-order ordinary differential equations, particularly those stemming from space finite element discretization of wave…

Numerical Analysis · Mathematics 2025-05-12 Paola F. Antonietti , Alberto Artoni , Gabriele Ciaramella , Ilario Mazzieri

Many problems in science and engineering can be represented by a set of partial differential equations (PDEs) through mathematical modeling. Mechanism-based computation following PDEs has long been an essential paradigm for studying topics…

Machine Learning · Computer Science 2022-11-21 Shudong Huang , Wentao Feng , Chenwei Tang , Jiancheng Lv