Search
Abstract
Utilization of fast surrogate models has become a viable alternative to direct handling of fullwave electromagnetic (EM) simulations in EM-driven design. Their purpose is to alleviate the difficulties related to high computational cost of multiple simulations required by the common numerical procedures such as parametric optimization or uncertainty quantification. Yet, conventional data-driven (or approximation) modeling techniques are severely affected by the curse of dimensionality. This is a serious limitation when it comes to modeling of highly nonlinear antenna characteristics. In practice, general-purpose surrogates can be rendered for the structures described by a few parameters within limited ranges thereof, which is grossly insufficient from the utility point of view. This paper proposes a novel modeling approach involving variable-fidelity EM simulations incorporated into the recently reported nested kriging modeling framework. Combining the information contained in the densely sampled low- and sparsely sampled highfidelity models is realized using co-kriging. The resulting surrogate exhibits the predictive power comparable to the model constructed using exclusively high-fidelity data while offering significantly reduced setup cost. The advantages over conventional surrogates are pronounced even further. The presented modeling procedure is demonstrated using two antenna examples and further validated through the application case studies.
Citations
-
5 1
CrossRef
-
0
Web of Science
-
5 1
Scopus
Authors (2)
Cite as
Full text
- Publication version
- Accepted or Published Version
- License
-
open in new tab
Keywords
Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
IEEE Access
no. 8,
pages 91048 - 91056,
ISSN: 2169-3536 - Language:
- English
- Publication year:
- 2020
- Bibliographic description:
- Pietrenko-Dąbrowska A., Kozieł S.: Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-Kriging// IEEE Access -Vol. 8, (2020), s.91048-91056
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/access.2020.2993951
- Verified by:
- Gdańsk University of Technology
seen 123 times