Skip to main navigation Skip to search Skip to main content

Fast evaluation of artificial boundary conditions for advection diffusion equations

  • Ting Sun
  • , Jilu Wang*
  • , Chunxiong Zheng
  • *Corresponding author for this work
  • Xinjiang University
  • China Academy of Engineering Physics
  • Tsinghua University

Research output: Contribution to journalArticlepeer-review

Abstract

An artificial boundary method is developed for solving the one-dimensional advection diffusion equation in the real line. In order to construct a fully discrete fast numerical algorithm with rigorous error analysis, we start with the two-step backward difference formula for time discretization of the advection diffusion equation in the whole real line. Then, we use the discrete analogue of the Laplace transform to derive a second-order time-stepping scheme in a bounded domain equipped with a discrete artificial boundary condition (ABC). The Galerkin finite element method is used for spatial discretization. To expedite the evaluation of time convolution involved in the discrete ABC, we propose a fast algorithm based on the best rational approximation of square root function in subdomains of the complex plane. An estimate for this best rational approximation enables us to prove optimal-order convergence of the fully discrete numerical scheme (integrating the fast approximation algorithm). Several numerical examples are provided to illustrate the convergence of numerical solutions and the effectiveness of the proposed fast approximation algorithm.

Original languageEnglish
Pages (from-to)3530-3557
Number of pages28
JournalSIAM Journal on Numerical Analysis
Volume58
Issue number6
DOIs
StatePublished - 18 Dec 2020
Externally publishedYes

Keywords

  • Advection diffusion equation
  • Artificial boundary method
  • Error estimates
  • Fast algorithm
  • Rational approximation

Fingerprint

Dive into the research topics of 'Fast evaluation of artificial boundary conditions for advection diffusion equations'. Together they form a unique fingerprint.

Cite this