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Cost-Efficient Bi-Layer Modeling of Antenna Input Characteristics Using Gradient Kriging Surrogates

Cost-Efficient Bi-Layer Modeling of Antenna Input Characteristics Using Gradient Kriging Surrogates


Title: Cost-Efficient Bi-Layer Modeling of Antenna Input Characteristics Using Gradient Kriging Surrogates
Author: Pietrenko-Dabrowska, Anna
Koziel, Slawomir   orcid.org/0000-0002-0584-4427
Al-Hasan, Mu'ath
Date: 2020
Language: English
Scope: 140831-140839
University/Institute: Háskólinn í Reykjavík
Reykjavik University
School: Tæknisvið (HR)
School of Technology (RU)
Department: Verkfræðideild (HR)
Department of Engineering (RU)
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2020.3013616
Subject: General Engineering; General Materials Science; General Computer Science; Antenna modeling; Surrogate modeling; Two-stage modeling; Gradient kriging; Domain confinement; Simulation-driven design; Design optimization; Verkfræði; Efnisfræði; Tölvunarfræði; Loftnet; Hönnun; Líkanagerð; Hermilíkön; Bestun
URI: https://hdl.handle.net/20.500.11815/2177

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Citation:

Pietrenko-Dabrowska, A., Koziel, S., & Al-Hasan, M. (2020). Cost-Efficient Bi-Layer Modeling of Antenna Input Characteristics Using Gradient Kriging Surrogates. Ieee Access, 8, 140831–140839. https://doi.org/10.1109/ACCESS.2020.3013616

Abstract:

Over the recent years, surrogate modeling has been playing an increasing role in the design of antenna structures. The main incentive is to mitigate the issues related to high cost of electromagnetic (EM)-based procedures. Among the various techniques, approximation surrogates are the most popular ones due to their flexibility and easy access. Notwithstanding, data-driven modeling of antenna characteristics is associated with serious practical issues, the primary one being the curse of dimensionality, particularly troublesome due to typically high nonlinearity of antenna responses. This limits applicability of conventional surrogates to simple structures described by a few parameters within narrow ranges thereof, which is grossly insufficient from the point of view of design utility. Many of these issues can be alleviated by the recently proposed constrained modeling techniques that restrict the surrogate domain to regions containing high-quality designs with respect to the relevant performance figures, which are identified using the pre-optimized reference designs at an extra computational effort. This paper proposes a methodology based on gradient-enhanced kriging (GEK). It enables a considerable reduction of the number of reference points required to construct the inverse surrogate (employed in surrogate model definition) by incorporating the sensitivity data into the nested kriging framework. Using two antenna examples, it is demonstrated to yield significant savings in terms of the surrogate model setup cost as compared to both conventional modeling methods and the original nested kriging.

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This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.

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