Adaptive unscented transform for uncertainty quantification in EMC large-scale systems

Abstract

Purpose

The purpose of this paper is to introduce a novel methodology for uncertainty quantification in large-scale systems. It is a non-intrusive approach based on the unscented transform (UT) but it requires far less simulations from a EM solver for certain models.

Design/methodology/approach

The methodology of uncertainty propagation is carried out adaptively instead of considering all input variables. First, a ranking of input variables is determined and after a classical UT is applied successively considering each time one more input variable. The convergence is reached once the most important variables were considered.

Findings

The adaptive UT can be an efficient alternative of uncertainty propagation for large dimensional systems.

Originality/value

The classical UT is unfeasible for large-scale systems. This paper presents one new possibility to use this stochastic collocation method for systems with large number of input dimensions.

Citation

Ferber, M., Vollaire, C., Krähenbühl, L. and Antônio Vasconcelos, J. (2014), "Adaptive unscented transform for uncertainty quantification in EMC large-scale systems", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 33 No. 3, pp. 914-926. https://doi.org/10.1108/COMPEL-10-2012-0212