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Performance-driven yield optimization of high-frequency structures by kriging surrogates

Abstract

Uncertainty quantification is an important aspect of engineering design, as manufacturing toler-ances may affect the characteristics of the structure. Therefore, quantification of these effects is in-dispensable for adequate assessment of the design quality. Toward this end, statistical analysis is performed, for reliability reasons, using full-wave electromagnetic (EM) simulations. Still, the computational expenditures associated with EM-driven statistical analysis often turn out to be unendurable. Recently, a performance-driven modeling technique has been proposed that may be employed for uncertainty quantification purposes, and enable circumventing the aforementioned difficulties. Capitalizing on this idea, this paper discusses a procedure for fast and simple surro-gate-based yield optimization of high-frequency structures. The main concept of the approach is a tailored definition of the surrogate domain, which is based on a couple of pre-optimized designs that reflect the directions featuring maximum variability of the circuit responses with respect to its dimensions. A compact size of such a domain allows for constructing an accurate metamodel therein using moderate numbers of training samples, and subsequently employ it to enhance the yield. The implementation details are dedicated to a particular type of device. Results obtained for a ring-slot antenna and a miniaturized rat-race coupler imply that the cost of yield optimization process can be reduced to few dozens of EM analyses.

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Keywords

Details

Category:
Articles
Type:
artykuły w czasopismach
Published in:
Applied Sciences-Basel no. 12,
ISSN: 2076-3417
Language:
English
Publication year:
2022
Bibliographic description:
Pietrenko-Dąbrowska A., Kozieł P.: Performance-driven yield optimization of high-frequency structures by kriging surrogates// Applied Sciences-Basel -Vol. 12,iss. 7 (2022), s.3697-
DOI:
Digital Object Identifier (open in new tab) 10.3390/app12073697
Sources of funding:
  • COST_FREE
Verified by:
Gdańsk University of Technology

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