中文版 | English
Title

The scalar auxiliary variable (SAV) approach for gradient flows

Author
Corresponding AuthorXu, Jie
Publication Years
2018-01-15
DOI
Source Title
ISSN
0021-9991
EISSN
1090-2716
Volume353Pages:407-416
Abstract

We propose a new approach, which we term as scalar auxiliary variable (SAV) approach, to construct efficient and accurate time discretization schemes for a large class of gradient flows. The SAV approach is built upon the recently introduced IEQ approach. It enjoys all advantages of the IEQ approach but overcomes most of its shortcomings. In particular, the SAV approach leads to numerical schemes that are unconditionally energy stable and extremely efficient in the sense that only decoupled equations with constant coefficients need to be solved at each time step. The scheme is not restricted to specific forms of the nonlinear part of the free energy, so it applies to a large class of gradient flows. Numerical results are presented to show that the accuracy and effectiveness of the SAV approach over the existing methods. (C) 2017 Elsevier Inc. All rights reserved.

Keywords
URL[Source Record]
Indexed By
SCI ; EI
Language
English
Important Publications
ESI Highly Cited Papers
SUSTech Authorship
Others
Funding Project
NSFC[11371298] ; NSFC[11421110001] ; NSFC[91630204] ; NSFC[51661135011]
WOS Research Area
Computer Science ; Physics
WOS Subject
Computer Science, Interdisciplinary Applications ; Physics, Mathematical
WOS Accession No
WOS:000418229800018
Publisher
EI Accession Number
20201708551146
EI Keywords
Numerical methods
ESI Classification Code
Thermodynamics:641.1 ; Numerical Methods:921.6
ESI Research Field
PHYSICS
Data Source
Web of Science
Citation statistics
Cited Times [WOS]:436
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/28161
DepartmentDepartment of Mathematics
工学院_材料科学与工程系
Affiliation
1.Purdue Univ, Dept Math, W Lafayette, IN 47907 USA
2.Xiamen Univ, Fujian Prov Key Lab Math Modeling & High Performa, Xiamen, Peoples R China
3.Xiamen Univ, Sch Math Sci, Xiamen, Peoples R China
4.Southern Univ Sci & Technol, Dept Math, Shenzhen, Peoples R China
Recommended Citation
GB/T 7714
Shen, Jie,Xu, Jie,Yang, Jiang. The scalar auxiliary variable (SAV) approach for gradient flows[J]. JOURNAL OF COMPUTATIONAL PHYSICS,2018,353:407-416.
APA
Shen, Jie,Xu, Jie,&Yang, Jiang.(2018).The scalar auxiliary variable (SAV) approach for gradient flows.JOURNAL OF COMPUTATIONAL PHYSICS,353,407-416.
MLA
Shen, Jie,et al."The scalar auxiliary variable (SAV) approach for gradient flows".JOURNAL OF COMPUTATIONAL PHYSICS 353(2018):407-416.
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