A Dimension-reduced Sparse Grid Strategy for Stochastic Collocation Method in EMC Software

Abstract

Stochastic Collocation Method (SCM), a prevailing uncertainty analysis method, has been successfully implemented in Electromagnetic Compatibility (EMC) simulation, especially in EMC commercial software. However, the “curse of dimensionality” problem (dimensionality means the number of uncertain variables) limits the application of the SCM. This paper proposes a novel sparse grid strategy in order to improve the computational efficiency of the SCM, especially in high dimensionality case. In the proposed strategy, it is revealed that the number of the collocation points is in proportion to the dimensionality. By simulating two shielding effectiveness analysis examples in CST software, the feasibility of the proposed method can be presented clearly, with the help of the Feature Selective Validation method.

Description

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.

Keywords

Stochastic Collocation Method, Uncertainty Analysis, Sparse Grid Strategy, EMC commercial software, Feature Selective Validation

Citation

Bai, J., Zhang, G., Duffy, A. and Wang, L. (2017) A Dimension-reduced Sparse Grid Strategy for Stochastic Collocation Method in EMC Software. IEEE Trans on EMC, 60 (1), pp. 218-224

Rights

Research Institute

Institute of Engineering Sciences (IES)