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题名

The scalar auxiliary variable (SAV) approach for gradient flows

作者
通讯作者Xu, Jie
发表日期
2018-01-15
DOI
发表期刊
ISSN
0021-9991
EISSN
1090-2716
卷号353页码:407-416
摘要

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.

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相关链接[来源记录]
收录类别
SCI ; EI
语种
英语
重要成果
ESI高被引
学校署名
其他
资助项目
NSFC[11371298] ; NSFC[11421110001] ; NSFC[91630204] ; NSFC[51661135011]
WOS研究方向
Computer Science ; Physics
WOS类目
Computer Science, Interdisciplinary Applications ; Physics, Mathematical
WOS记录号
WOS:000418229800018
出版者
EI入藏号
20201708551146
EI主题词
Numerical methods
EI分类号
Thermodynamics:641.1 ; Numerical Methods:921.6
ESI学科分类
PHYSICS
来源库
Web of Science
引用统计
被引频次[WOS]:606
成果类型期刊论文
条目标识符//www.snoollab.com/handle/2SGJ60CL/28161
专题理学院_数学系
工学院_材料科学与工程系
作者单位
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
推荐引用方式
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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