Journal article
A Well-Balanced Stochastic Galerkin Method for Scalar Hyperbolic Balance Laws with Random Inputs
Journal of scientific computing, Vol.67(3), pp.1198-1218
06/01/2016
DOI: 10.1007/s10915-015-0124-2
Abstract
We propose a generalized polynomial chaos based stochastic Galerkin methods for scalar hyperbolic balance laws with random geometric source terms or random initial data. This method is well-balanced (WB), in the sense that it captures the stochastic steady state solution with high order accuracy. The framework of the stochastic WB schemes is presented in details, along with several numerical examples to illustrate their accuracy and effectiveness. The goal of this paper is to show that the stochastic WB scheme yields a more accurate numerical solution at steady state than the non-WB ones.
Details
- Title: Subtitle
- A Well-Balanced Stochastic Galerkin Method for Scalar Hyperbolic Balance Laws with Random Inputs
- Creators
- Shi Jin - University of Wisconsin–MadisonDongbin Xiu - University of UtahXueyu Zhu - University of Utah
- Resource Type
- Journal article
- Publication Details
- Journal of scientific computing, Vol.67(3), pp.1198-1218
- Publisher
- SPRINGER/PLENUM PUBLISHERS
- DOI
- 10.1007/s10915-015-0124-2
- ISSN
- 0885-7474
- eISSN
- 1573-7691
- Number of pages
- 21
- Grant note
- 91330203 / National Science Foundation of China AFOSR DOE 1107291; 1107291: RNMS "KI-Net" / NSF DMS
- Language
- English
- Date published
- 06/01/2016
- Academic Unit
- Mathematics
- Record Identifier
- 9984240860702771
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