Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Computationally efficient adaptive time step method for the Cahn-Hilliard equation

Authors
Li, YibaoChoi, YonghoKim, Junseok
Issue Date
15-4월-2017
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Keywords
Cahn-Hilliard equation; Adaptive time-stepping method; Unconditionally stable scheme
Citation
COMPUTERS & MATHEMATICS WITH APPLICATIONS, v.73, no.8, pp.1855 - 1864
Indexed
SCIE
SCOPUS
Journal Title
COMPUTERS & MATHEMATICS WITH APPLICATIONS
Volume
73
Number
8
Start Page
1855
End Page
1864
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/83752
DOI
10.1016/j.camwa.2017.02.021
ISSN
0898-1221
Abstract
In this work, we propose a fast and efficient adaptive time step procedure for the Cahn Hilliard equation. The temporal evolution of the Cahn Hilliard equation has multiple time scales. For spinodal decomposition simulation, an initial random perturbation evolves on a fast time scale, and later coarsening evolves on a very slow time scale. Therefore, if a small time step is used to capture the fast dynamics, the computation is quite costly. On the other hand, if a large time step is used, fast time evolutions may be missed. Hence, it is essential to use an adaptive time step method to simulate phenomena with multiple time scales. The proposed time adaptivity algorithm is based on the discrete maximum norm of the difference between two consecutive time step numerical solutions. Numerical experiments in one, two, and three dimensions are presented to demonstrate the performance and effectiveness of the adaptive time-stepping algorithm. (C) 2017 Elsevier Ltd. All rights reserved.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Science > Department of Mathematics > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kim, Jun seok photo

Kim, Jun seok
이과대학 (수학과)
Read more

Altmetrics

Total Views & Downloads

BROWSE