Global Sensitivity Analysis Using a Kriging Metamodel for EM Design Problems With Functional Outputs

Abstract

A global sensitivity analysis (SA) method enhanced with a kriging surrogate model is considered in this work. To decide on the importance of many model parameters in the case of a functional output, the Sobol’ sensitivity indices—being functions of an independent variable—are to be calculated over a domain of interest. Since for expensive-to-evaluate models obtaining such a sensitivity map is highly computationally demanding, the number of required samples is reduced by a kriging approximation combined with an adaptive sampling strategy that exploits the probability information provided by the kriging model. The advantages of the approach are demonstrated through the example of an electromagnetic interference (EMI) filter.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 21 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.