Workgreen2014

Non intrusive Polynomial Chaos-based stochastic macromodeling of multiport systems

Domenico Spina · Francesco Ferranti · Giulio Antonini · Tom Dhaene · Luc F. Knockaert

16 citations0/0 files storedIEEE Workshop on Signal and Power Integrity

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Probabilistic and Robust Engineering Design Microwave Engineering and Waveguides Electromagnetic Simulation and Numerical Methods

Abstract

We present a novel technique to efficiently perform the variability analysis of electromagnetic systems. The proposed method calculates a Polynomial Chaos-based macromodel of the system transfer function that includes its statistical properties. The combination of a non-intrusive Polynomial Chaos approach with the Vector Fitting algorithm allows to describe the system variability features with accuracy and efficiency. The results of the variability analysis performed with the proposed method are verified by means of comparison with respect to the standard Monte Carlo analysis.

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References

2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations 2009An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis 2009Recent Advances in Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Analysis and Design 2006Modeling Arbitrary Uncertainties Using Gram-Schmidt Polynomial Chaos 2011Stochastic Analysis of Multiconductor Cables and Interconnects 2011Parameters Variability Effects on Multiconductor Interconnects via Hermite Polynomial Chaos 2012Stochastic Modeling-Based Variability Analysis of On-Chip Interconnects 2012Variability Analysis of Multiport Systems Via Polynomial-Chaos Expansion

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2019A Predictor–Corrector Algorithm for Fast Polynomial Chaos-Based Uncertainty Quantification of Multi-Walled Carbon Nanotube Interconnects 2015Accurate polynomial chaos expansion for variability analysis using optimal design of experiments

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