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Expedited Yield Optimization of Narrow- and Multi-Band Antennas Using Performance-Driven Surrogates

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dc.contributor Háskólinn í Reykjavík
dc.contributor Reykjavik University
dc.contributor.author Pietrenko-Dabrowska, Anna
dc.contributor.author Koziel, Slawomir
dc.contributor.author Al-Hasan, Muath
dc.date.accessioned 2020-11-30T14:59:32Z
dc.date.available 2020-11-30T14:59:32Z
dc.date.issued 2020
dc.identifier.citation Pietrenko-Dabrowska, A., Koziel, S., & Al-Hasan, M. (2020). Expedited Yield Optimization of Narrow- and Multi-Band Antennas Using Performance-Driven Surrogates. Ieee Access, 8, 143104–143113. https://doi.org/10.1109/ACCESS.2020.3013985
dc.identifier.issn 2169-3536
dc.identifier.uri https://hdl.handle.net/20.500.11815/2257
dc.description Publisher's version (útgefin grein)
dc.description.abstract Uncertainty quantification is an important aspect of engineering design, also pertaining to the development and performance evaluation of antenna systems. Manufacturing tolerances as well as other types of uncertainties, related to material parameters (e.g., substrate permittivity) or operating conditions (e.g., bending) may affect the antenna characteristics. In the case of narrow- or multi-band antennas, this usually leads to frequency shifts of the operating bands. Quantifying these effects is imperative to adequately assess the design quality, either in terms of the statistical moments of the performance parameters or the yield. Reducing the antenna sensitivity to parameter deviations is even more essential when increasing the probability of the system satisfying the prescribed requirements is of concern. The prerequisite of such procedures is statistical analysis, normally carried out at the level of full-wave electromagnetic (EM) analysis. While necessary to ensure reliability, it entails considerable computational expenses, often prohibitive. Following the recently fostered concept of constrained modeling, this paper proposes a simple technique for rapid surrogate-assisted yield optimization of narrow- and multi-band antennas. The keystone of the approach is an appropriate definition of the optimization domain. This is realized by considering a few pre-optimized designs that represent the directions of the major changes of the antenna resonant frequencies and operating bands. Due to a small volume of such a domain, an accurate replacement model can be established therein using a small number of training samples, and employed to improve the antenna yield. Verification results obtained for a ring-slot antenna, a dual-band and a triple-band uniplanar dipoles indicate that the optimization process can be accomplished at low cost of a few dozen of EM simulations: 62, 74 and 132 EM simulations, respectively. Result reliability is validated through comparisons with EM-based Monte Carlo simulations.
dc.description.sponsorship This work was supported in part by the Icelandic Centre for Research (RANNIS) under Grant 206606051, in part by the National Science Centre of Poland under Grant 2017/27/B/ST7/00563, and in part by the Abu-Dhabi Department of Education and Knowledge (ADEK) Award for Research Excellence, in 2019, under Grant AARE19-245.
dc.format.extent 143104-143113
dc.language.iso en
dc.publisher Institute of Electrical and Electronics Engineers (IEEE)
dc.rights info:eu-repo/semantics/openAccess
dc.subject General Engineering
dc.subject General Materials Science
dc.subject General Computer Science
dc.subject Uncertainty quantification
dc.subject Tolerance-aware design
dc.subject Yield optimization
dc.subject Multi-band antennas
dc.subject Performance-driven modeling
dc.subject Verkfræði
dc.subject Efnisfræði
dc.subject Tölvunarfræði
dc.subject Magngreining
dc.subject Óvissa
dc.subject Þolmörk
dc.subject Hönnun
dc.subject Bestun
dc.subject Loftnet
dc.subject Líkanagerð
dc.title Expedited Yield Optimization of Narrow- and Multi-Band Antennas Using Performance-Driven Surrogates
dc.type info:eu-repo/semantics/article
dcterms.license This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
dc.description.version "Peer Reviewed"
dc.identifier.journal IEEE Access
dc.identifier.doi 10.1109/ACCESS.2020.3013985
dc.relation.url http://xplorestaging.ieee.org/ielx7/6287639/8948470/09154678.pdf?arnumber=9154678
dc.contributor.department Verkfræðideild (HR)
dc.contributor.department Department of Engineering (RU)
dc.contributor.department Engineering Optimization & Modeling Center (EOMC)
dc.contributor.school Tæknisvið (HR)
dc.contributor.school School of Technology (RU)

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