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Status已发表Published
TitleEfficient Stochastic Galerkin Methods for Maxwell's Equations with Random Inputs
Creator
Date Issued2019
Source PublicationJournal of Scientific Computing
ISSN8857474
Volume80Issue:1Pages:248-267
Abstract

In this paper, we are concerned with the stochastic Galerkin methods for time-dependent Maxwell’s equations with random input. The generalized polynomial chaos approach is first adopted to convert the original random Maxwell’s equation into a system of deterministic equations for the expansion coefficients (the Galerkin system). It is shown that the stochastic Galerkin approach preserves the energy conservation law. Then, we propose a finite element approach in the physical space to solve the Galerkin system, and error estimates is presented. For the time domain approach, we propose two discrete schemes, namely, the Crank–Nicolson scheme and the leap-frog type scheme. For the Crank–Nicolson scheme, we show the energy preserving property for the fully discrete scheme. While for the classic leap-frog scheme, we present a conditional energy stability property. It is well known that for the stochastic Galerkin approach, the main challenge is how to efficiently solve the coupled Galerkin system. To this end, we design a modified leap-frog type scheme in which one can solve the coupled system in a decouple way—yielding a very efficient numerical approach. Numerical examples are presented to support the theoretical finding.

KeywordFinite element method Maxwell's equations Polynomial chaos methods Random inputs Stochastic Galerkin
DOI10.1007/s10915-019-00936-z
URLView source
Indexed BySCIE
Language英语English
WOS Research AreaMathematics
WOS SubjectMathematics, Applied
WOS IDWOS:000468983100009
SciVal Topic ProminenceT.1942
Citation statistics
Cited Times:11[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/2099
CollectionResearch outside affiliated institution
Corresponding AuthorLi, Jichun
Affiliation
1.Department of Mathematical Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154-4020, United States
2.Department of Mathematics, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
3.LSEC, Institute of Computational Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China
Recommended Citation
GB/T 7714
Fang, Zhiwei,Li, Jichun,Tang, Taoet al. Efficient Stochastic Galerkin Methods for Maxwell's Equations with Random Inputs[J]. Journal of Scientific Computing, 2019, 80(1): 248-267.
APA Fang, Zhiwei, Li, Jichun, Tang, Tao, & Zhou, Tao. (2019). Efficient Stochastic Galerkin Methods for Maxwell's Equations with Random Inputs. Journal of Scientific Computing, 80(1), 248-267.
MLA Fang, Zhiwei,et al."Efficient Stochastic Galerkin Methods for Maxwell's Equations with Random Inputs". Journal of Scientific Computing 80.1(2019): 248-267.
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