An Electromagnetic Compatibility Problem via Unscented Transform and Stochastic Collocation Methods

Authors

  • S. Lalléchère Clermont University Blaise Pascal University, LASMEA, Clermont-Ferrand, 63000, France
  • P. Bonnet Clermont University Blaise Pascal University, LASMEA, Clermont-Ferrand, 63000, France
  • I. El Baba Clermont University Blaise Pascal University, LASMEA, Clermont-Ferrand, 63000, France
  • F. Paladian Clermont University Blaise Pascal University, LASMEA, Clermont-Ferrand, 63000, France

Keywords:

An Electromagnetic Compatibility Problem via Unscented Transform and Stochastic Collocation Methods

Abstract

This paper aims to illustrate the current interest about the use of stochastic techniques for electromagnetic compatibility (EMC) issues. This problem may be handled from various methods. First, we may focus on the Monte Carlo (MC) formalism but other techniques have been implemented more recently (the unscented transform, UT, or stochastic collocation, SC, for instance). This work deals with solving a stochastic EMC problem (transmission line) with the UT and SC techniques and to compare them with the reference MC results.

Downloads

Download data is not yet available.

Author Biography

S. Lalléchère, Clermont University Blaise Pascal University, LASMEA, Clermont-Ferrand, 63000, France

Sébastien Lalléchère received his Ph.D. degree
(2006) in Electromagnetism. Since 2007, heis an
assistant professor at Clermont Universityand is
interested in numerical methods for
electromagnetism.

References

N. Mishra and N. Gupta, “Quasi Monte Carlo

Integration Technique for Method of Moments

Solution of EFIE in Radiation Problems,”Applied

Computational Electromagnetic Society (ACES)

Journal, vol. 24, no. 3, pp. 306-311, June 2009.

L. De Menezes, A. Ajayi, C. Christopoulos, P.

Sewell, and G. A. Borges, “Efficient Computation

of Stochastic Electromagnetic Problems using

Unscented Transforms,” IET Sci. Mea. Tec., vol.

, no. 2, pp. 88-95, 2008.

L. De Menezes, D.W. P. Thomas, C.

Christopoulos, A. Ajayi, and P. Sewell, “TheUse

of Unscented Transforms for Statistical Analysis

in EM,” Proc. EMC Europe, 2008.

C. Chauvière, J. S. Hestaven, and L. C. Wilcox,

“Efficient Computation of RCS fromScatterers of

Uncertain Shapes,” IEEE Trans. On Ant. And

Prop., vol. 55, no. 5, pp. 1437-1448, May 2007.

P. S. Sumant, H. Wu, A. C. Cangellaris, and N. R.

Aluru, “A Sparse Grid Based Collocation Method

for Model Order Reduction of Finite Element

Approximations of Passive Electromagnetic

Devices under Uncertainty,” 2010 IEEE MTT-S

International, Anaheim, CA, USA, pp. 1652-1655,

May 2010.

V. Rannou, F. Brouaye, M. Hélier, and W.

Tabbara, “Kriging the Quantile: Application to a

Simple Transmission Line Model,” Inverse

Problems, vol. 18, pp. 37-48, 2002.

J. Foo and G.E. Karniadakis, “Multi-Element

Probabilistic Collocation Method in High

Dimensions,” J. Comp. Phys., vol. 229, no. 5, pp.

-1577, 2010.

A.C. Yucel, H. Bagci, and E. Michielsen, “An h-

Adaptative Stochastic Collocation Method for

Stochastic EMC/EMI Analysis,” Proc. IEEE APS,

Toronto, Canada, 2010.

P. Bonnet, F. Diouf, C. Chauvière,S. Lalléchère,

M. Fogli, and F. Paladian, “Numerical Simulation

of a Reverberation Chamber with aStochastic

Collocation Method,” CRAS, vol. 10, pp. 54-64,

F. Paladian, P. Bonnet, and S. Lalléchère,

“Modeling Complex Systems for EMC

Applications by Considering Uncertainties,” XXX

URSI General Assembly, Istanbul, Turkey, August

A. H. Stroud, “Remarks on theDisposition of

Points in Numerical Integration Formulas,” Math.

Tables Other Aids Comp., vol. 11, no. 3, pp. 1118-

, October 1957.

H. Bagci, A. C. Yucel, J. S. Hesthaven, and E.

Michielssen, “A Fast Stroud-Based Collocation

Method for Statistically Characterizing EMI/EMC

Phenomena on Complex Platforms,” IEEE Trans.

on EMC, vol. 51, no. 2, pp. 301-311, 2009.

Downloads

Published

2022-05-02

How to Cite

[1]
S. . Lalléchère, P. . Bonnet, I. E. . Baba, and F. . Paladian, “An Electromagnetic Compatibility Problem via Unscented Transform and Stochastic Collocation Methods”, ACES Journal, vol. 27, no. 2, pp. 94–101, May 2022.

Issue

Section

General Submission