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A Fast Polynomial Chaos Expansion for Uncertainty Quantification in Stochastic Electromagnetic Problems

Tomy, Gladwin Jos Kurupasseril and Vinoy, Kalarickaparambil Joseph (2019) A Fast Polynomial Chaos Expansion for Uncertainty Quantification in Stochastic Electromagnetic Problems. In: IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, 18 (10). pp. 2120-2124.

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Official URL: http:/dx.doi.org/10.1109/LAWP.2019.2938323

Abstract

Variations in material properties, boundary conditions, or the geometry can be expected in most electromagnetic problems. When these uncertainties in different regions of the model space are considered simultaneously, the stochastic dimensionality and the computational cost increase. Hence, uncertainty quantification in such problems is seldom attempted even though its quantification leads to a robust model. In this letter, a nonintrusive least square polynomial chaos expansion method is employed to quantify uncertainty due to stochastic variation of material properties. Using this method, the deviation from the mean performance for the transmission coefficient is obtained across the operational frequency range. The results compare well with Monte Carlo method and require just 1 & x0025; of its total computational time.

Item Type: Journal Article
Publication: IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS
Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Additional Information: Copyright of this article belongs to IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords: Finite-element method (FEM); generalized minimal residual (GMRES); high stochastic dimensionality; least square; nonintrusive; polynomial chaos expansion (PCE)
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 12 Dec 2019 10:25
Last Modified: 12 Dec 2019 10:25
URI: http://eprints.iisc.ac.in/id/eprint/63979

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