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Efficient variability analysis of electromagnetic systems via polynomial chaos and model order reduction

Domenico Spina (UGent) , Francesco Ferranti (UGent) , Giulio Antonini, Tom Dhaene (UGent) and Luc Knockaert (UGent)
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Abstract
We present a novel technique to perform the model-order reduction (MOR) of multiport systems under the effect of statistical variability of geometrical or electrical parameters. The proposed approach combines a deterministic MOR phase with the use of the Polynomial Chaos (PC) expansion to perform the variability analysis of the system under study very efficiently. The combination of MOR and PC techniques generates a final reduced-order model able to accurately perform stochastic computations and variability analysis. The novel proposed method guarantees a high-degree of flexibility, since different MOR schemes can be used and different types of modern electrical systems (e. g., filters and connectors) can be modeled. The accuracy and efficiency of the proposed approach is verified by means of two numerical examples and compared with other existing variability analysis techniques.
Keywords
Model-order reduction (MOR), GRIDS, multiport systems, polynomial chaos (PC), variability analysis (VA), IBCN

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Chicago
Spina, Domenico, Francesco Ferranti, Giulio Antonini, Tom Dhaene, and Luc Knockaert. 2014. “Efficient Variability Analysis of Electromagnetic Systems via Polynomial Chaos and Model Order Reduction.” Ieee Transactions on Components Packaging and Manufacturing Technology 4 (6): 1038–1051.
APA
Spina, D., Ferranti, F., Antonini, G., Dhaene, T., & Knockaert, L. (2014). Efficient variability analysis of electromagnetic systems via polynomial chaos and model order reduction. IEEE TRANSACTIONS ON COMPONENTS PACKAGING AND MANUFACTURING TECHNOLOGY, 4(6), 1038–1051.
Vancouver
1.
Spina D, Ferranti F, Antonini G, Dhaene T, Knockaert L. Efficient variability analysis of electromagnetic systems via polynomial chaos and model order reduction. IEEE TRANSACTIONS ON COMPONENTS PACKAGING AND MANUFACTURING TECHNOLOGY. 2014;4(6):1038–51.
MLA
Spina, Domenico, Francesco Ferranti, Giulio Antonini, et al. “Efficient Variability Analysis of Electromagnetic Systems via Polynomial Chaos and Model Order Reduction.” IEEE TRANSACTIONS ON COMPONENTS PACKAGING AND MANUFACTURING TECHNOLOGY 4.6 (2014): 1038–1051. Print.
@article{5730973,
  abstract     = {We present a novel technique to perform the model-order reduction (MOR) of multiport systems under the effect of statistical variability of geometrical or electrical parameters. The proposed approach combines a deterministic MOR phase with the use of the Polynomial Chaos (PC) expansion to perform the variability analysis of the system under study very efficiently. The combination of MOR and PC techniques generates a final reduced-order model able to accurately perform stochastic computations and variability analysis. The novel proposed method guarantees a high-degree of flexibility, since different MOR schemes can be used and different types of modern electrical systems (e. g., filters and connectors) can be modeled. The accuracy and efficiency of the proposed approach is verified by means of two numerical examples and compared with other existing variability analysis techniques.},
  author       = {Spina, Domenico and Ferranti, Francesco and Antonini, Giulio and Dhaene, Tom and Knockaert, Luc},
  issn         = {2156-3950},
  journal      = {IEEE TRANSACTIONS ON COMPONENTS PACKAGING AND MANUFACTURING TECHNOLOGY},
  language     = {eng},
  number       = {6},
  pages        = {1038--1051},
  title        = {Efficient variability analysis of electromagnetic systems via polynomial chaos and model order reduction},
  url          = {http://dx.doi.org/10.1109/TCPMT.2014.2312455},
  volume       = {4},
  year         = {2014},
}

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