Quantifying Uncertainty for Ideal MHD Based on A Stochastic Galerkin Approach

Speaker:   Prof. Xinghui Zhong 

Time:       14:00-15:00, Sep. 11

Location:  SIST 1A 108

Host:       Prof. Qifeng Liao

Abstract:                                                                                                                                                                

We investigate the ideal magnetohydrodynamic (MHD) equations with random inputs based on generalized polynomial chaos (gPC) stochastic Galerkin approximation.  A special treatment with symmetrization is carried out for the gPC stochastic Galerkin method so that the resulting deterministic gPC Galerkin system is provably symmetric hyperbolic in the spatially one-dimensional case. We discretize the hyperbolic gPC Galerkin system with a high-order path-conservative finite volume weighted essentially non-oscillatory scheme in space and a third-order total variation diminishing  Runge-Kutta method in time. The method is also extended to two spatial dimensions via the operator splitting technique. Several numerical examples are provided to illustrate the accuracy and effectiveness of the numerical scheme.

Bio:

仲杏慧：浙江大学特聘研究员。2007年于中国科技大学获得理学学士学位，2012年博士毕业于布朗大学，导师为舒其望教授。随后在美国密歇根州立大学，犹他大学做博士后。主要研究方向包括间断有限元方法等高阶数值方法的分析与应用、科学计算及不确定性量化等领域。

SIST-Seminar 18198