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The accuracy of solving partial differential equations (PDEs) on coarse grids is greatly affected by the choice of discretization schemes. In this work, we propose to learn time integration schemes based on neural networks which satisfy…

Numerical Analysis · Mathematics 2023-10-17 Xinxin Yan , Zhideng Zhou , Xiaohan Cheng , Xiaolei Yang

Sequential numerical methods for integrating initial value problems (IVPs) can be prohibitively expensive when high numerical accuracy is required over the entire interval of integration. One remedy is to integrate in a parallel fashion,…

Numerical Analysis · Mathematics 2022-09-26 Kamran Pentland , Massimiliano Tamborrino , T. J. Sullivan , James Buchanan , L. C. Appel

Mathematical models that couple partial differential equations (PDEs) and spatially distributed ordinary differential equations (ODEs) arise in biology, medicine, chemistry and many other fields. In this paper we discuss an extension to the…

Numerical Analysis · Mathematics 2017-08-28 Patrick E. Farrell , Johan E. Hake , Simon W. Funke , Marie E. Rognes

We examine numerical rounding errors of some deterministic solvers for systems of ordinary differential equations (ODEs). We show that the accumulation of rounding errors results in a solution that is inherently random and we obtain the…

Numerical Analysis · Mathematics 2009-03-13 Sebastian Mosbach , Amanda G. Turner

Electro-quasistatic field problems involving nonlinear materials are commonly discretized in space using finite elements. In this paper, it is proposed to solve the resulting system of ordinary differential equations by an explicit…

Computational Engineering, Finance, and Science · Computer Science 2017-09-26 Christian Richter , Sebastian Schöps , Markus Clemens

Ordinary differential equation (ODE) models are widely used to describe chemical or biological processes. This article considers the estimation and assessment of such models on the basis of time-course data. Due to experimental limitations,…

Molecular Networks · Quantitative Biology 2023-02-14 Samuel W. K. Wong , Shihao Yang , S. C. Kou

New implicit and implicit-explicit time-stepping methods for the wave equation in second-order form are described with application to two and three-dimensional problems discretized on overset grids. The implicit schemes are single step,…

Numerical Analysis · Mathematics 2024-04-24 Allison M. Carson , Jeffrey W. Banks , William D. Henshaw , Donald W. Schwendeman

The objective of this paper is to prove the convergence of a linear implicit multi-step numerical method for ordinary differential equations. The algorithm is obtained via Taylor approximations. The convergence is proved following the…

Chaotic Dynamics · Physics 2011-03-08 Marius-F. Danca

We study first-order optimization methods obtained by discretizing ordinary differential equations (ODEs) corresponding to Nesterov's accelerated gradient methods (NAGs) and Polyak's heavy-ball method. We consider three discretization…

Optimization and Control · Mathematics 2019-11-05 Bin Shi , Simon S. Du , Weijie J. Su , Michael I. Jordan

An efficient and reliable stress computation algorithm is presented, which is based on implicit integration of the local evolution equations of multiplicative finite-strain plasticity/viscoplasticity. The algorithm is illustrated by an…

Numerical Analysis · Mathematics 2016-05-25 A. V. Shutov

In recent years, the embedding approach for solving switched optimal control problems has been developed in a series of papers. However, the embedding approach, which advantageously converts the hybrid optimal control problem to a classical…

Optimization and Control · Mathematics 2018-04-04 Richard Meyer , Miloš Žefran , Raymond A. DeCarlo

Much recent interest has focused on the design of optimization algorithms from the discretization of an associated optimization flow, i.e., a system of differential equations (ODEs) whose trajectories solve an associated optimization…

Optimization and Control · Mathematics 2022-02-02 Pedro Cisneros-Velarde , Francesco Bullo

A single-step high-order implicit time integration scheme with controllable numerical dissipation at high frequencies is presented for the transient analysis of structural dynamic problems. The amount of numerical dissipation is controlled…

Numerical Analysis · Mathematics 2023-09-29 Chongmin Song , Xiaoran Zhang , Sascha Eisenträger , Ankit Ankit

As a method of universal approximation deep neural networks (DNNs) are capable of finding approximate solutions to problems posed with little more constraints than a suitably-posed mathematical system and an objective function.…

Numerical Analysis · Mathematics 2022-03-02 D. W. Crews

Matrix-free finite element implementations for large applications provide an attractive alternative to standard sparse matrix data formats due to the significantly reduced memory consumption. Here, we show that they are also competitive…

Computational Engineering, Finance, and Science · Computer Science 2020-03-19 Daniel Drzisga , Ulrich Rüde , Barbara Wohlmuth

We present a multirate method that is particularly suited for integrating the systems of Ordinary Differential Equations (ODEs) that arise in step models of surface evolution. The surface of a crystal lattice, that is slightly miscut from a…

Numerical Analysis · Mathematics 2008-10-15 Pak-Wing Fok , Rodolfo R. Rosales

Neural ordinary differential equations (ODEs) have been attracting increasing attention in various research domains recently. There have been some works studying optimization issues and approximation capabilities of neural ODEs, but their…

Machine Learning · Computer Science 2022-03-04 Hanshu Yan , Jiawei Du , Vincent Y. F. Tan , Jiashi Feng

We consider a sparse grid collocation method in conjunction with a time discretization of the differential equations for computing expectations of functionals of solutions to differential equations perturbed by time-dependent white noise.…

Numerical Analysis · Mathematics 2015-05-18 Z. Zhang , M. V. Tretyakov , B. Rozovskii , G. E. Karniadakis

We present an algorithm for the rapid numerical integration of smooth, time-periodic differential equations with small nonlinearity, particularly suited to problems with small dissipation. The emphasis is on speed without compromising…

Numerical Analysis · Mathematics 2015-06-23 Michele V. Bartuccelli , Jonathan H. B. Deane , Guido Gentile

We propose an effective and flexible way to implement 2D and 3D elastoplastic problems in MATLAB using fully vectorized codes. Our technique is applied to a broad class of the problems including perfect plasticity or plasticity with…

Numerical Analysis · Mathematics 2018-09-07 Martin Čermák , Stanislav Sysala , Jan Valdman