Uncertainty Quantification for a Microstrip Self-Biased Ku-band Circulator

Yoan Le Noane (1, 2) , Evan Roué (3, 1, 2) , Norbert Parker (3, 1, 2) , Mihai Telescu (2, 4, 1) , Vincent Laur (3, 1, 2) , Noël Tanguy (2, 4, 1)

1 UBO - Université de Brest
2 Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
3 Lab-STICC_SMART - Equipe Smart Materials and Related Technologies
4 Lab-STICC_PIM - Equipe PIM

This paper focuses on uncertainty quantification for a Y-junction circulator. In the process of transitioning from prototyping to mass-production it is very important to understand how the uncertainties affecting input design parameters impact crucial features of the device behavior such as bandwidth or resonant frequency. This paper demonstrates the construction of a polynomial chaos expansion metamodel and its use in performing sensitivity analysis. The impact of the various sources of uncertainty affecting the circulator's behavior is quantified and the results are discussed.

Keywords: circulator; polynomial chaos expansion; self-biased device; stochastic analysis

Domains: Electronics; Statistics [stat]

Yoan Le Noane, Evan Roué, Norbert Parker, Mihai Telescu, Vincent Laur, et al.. Uncertainty Quantification for a Microstrip Self-Biased Ku-band Circulator. Asia-Pacific Microwave Conference (APMC2023), Dec 2023, Taipei, Taiwan. ⟨hal-04404655⟩