Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-Kriging
Utilization of fast surrogate models has become a viable alternative to direct handling of full-wave 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 proced...
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9091118/ |
| _version_ | 1818616706127364096 |
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| author | Anna Pietrenko-Dabrowska Slawomir Koziel |
| author_facet | Anna Pietrenko-Dabrowska Slawomir Koziel |
| author_sort | Anna Pietrenko-Dabrowska |
| collection | DOAJ |
| description | Utilization of fast surrogate models has become a viable alternative to direct handling of full-wave 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 high-fidelity 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. |
| first_indexed | 2024-12-16T16:54:04Z |
| format | Article |
| id | doaj.art-ee6595b352c5469293c9d2f97d40e6cf |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T16:54:04Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-ee6595b352c5469293c9d2f97d40e6cf2022-12-21T22:23:56ZengIEEEIEEE Access2169-35362020-01-018910489105610.1109/ACCESS.2020.29939519091118Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-KrigingAnna Pietrenko-Dabrowska0https://orcid.org/0000-0003-2319-6782Slawomir Koziel1https://orcid.org/0000-0002-9063-2647Faculty of Electronics, Telecommunications, and Informatics, Gdansk University of Technology, Gdansk, PolandFaculty of Electronics, Telecommunications, and Informatics, Gdansk University of Technology, Gdansk, PolandUtilization of fast surrogate models has become a viable alternative to direct handling of full-wave 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 high-fidelity 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.https://ieeexplore.ieee.org/document/9091118/Antenna designsurrogate modelingkriging interpolationco-krigingelectromagnetic (EM) simulation |
| spellingShingle | Anna Pietrenko-Dabrowska Slawomir Koziel Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-Kriging IEEE Access Antenna design surrogate modeling kriging interpolation co-kriging electromagnetic (EM) simulation |
| title | Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-Kriging |
| title_full | Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-Kriging |
| title_fullStr | Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-Kriging |
| title_full_unstemmed | Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-Kriging |
| title_short | Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-Kriging |
| title_sort | antenna modeling using variable fidelity em simulations and constrained co kriging |
| topic | Antenna design surrogate modeling kriging interpolation co-kriging electromagnetic (EM) simulation |
| url | https://ieeexplore.ieee.org/document/9091118/ |
| work_keys_str_mv | AT annapietrenkodabrowska antennamodelingusingvariablefidelityemsimulationsandconstrainedcokriging AT slawomirkoziel antennamodelingusingvariablefidelityemsimulationsandconstrainedcokriging |