Analysis of a printed circuit board with many uncertain variables by sparse polynomial chaos

Abstract : This communication deals with the uncertainty quantification in high dimensional problems. It introduces a metamodel based on the sparse polynomial chaos for the analysis of a printed circuit board, depending on many uncertain variables. This metamodel allows to estimate statistical quantities of an output with a relative low computational cost compared to Monte Carlo (MC) simulation. Results obtained have been validated by comparison with MC simulation. © 2017 IEEE.
Type de document :
Communication dans un congrès
2017 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization for RF, Microwave, and Terahertz Applications, NEMO 2017, May 2017, Nagoya, Japan. 〈10.1109/NEMO.2017.7964274〉
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https://hal-univ-rennes1.archives-ouvertes.fr/hal-01622684
Contributeur : Laurent Jonchère <>
Soumis le : mardi 24 octobre 2017 - 15:38:25
Dernière modification le : jeudi 5 avril 2018 - 12:30:20

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M. Larbi, I.S. Stievano, F.G. Canavero, P. Besnier. Analysis of a printed circuit board with many uncertain variables by sparse polynomial chaos. 2017 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization for RF, Microwave, and Terahertz Applications, NEMO 2017, May 2017, Nagoya, Japan. 〈10.1109/NEMO.2017.7964274〉. 〈hal-01622684〉

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