Archivio Istituzionale della RicercaThis 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.
Analysis of a printed circuit board with many uncertain variables by sparse polynomial chaos / Larbi, Mourad; Stievano, IGOR SIMONE; Canavero, Flavio; Besnier, Philippe. - STAMPA. - (2017), pp. 323-325. (Intervento presentato al convegno 2017 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization for RF, Microwave, and Terahertz Applications, NEMO 2017 tenutosi a esp nel 2017) [10.1109/NEMO.2017.7964274].
Analysis of a printed circuit board with many uncertain variables by sparse polynomial chaos
LARBI, MOURAD;STIEVANO, IGOR SIMONE;CANAVERO, Flavio;
2017
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.
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https://hdl.handle.net/11583/2687783
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