Uncertainty Quantification and Global Sensitivity Analysis of Radiated Susceptibility in Multiconductor Transmission Lines using Adaptive Sparse Polynomial Chaos Expansions
DOI:
https://doi.org/10.13052/2021.ACES.J.361004Keywords:
Adaptive sparse polynomial chaos expansion, Multiconductor transmission lines (MTLs), Radiated susceptibility, Uncertainty quantizationAbstract
This study analyzes the uncertainties of the radiated susceptibility in multiconductor transmission lines (MTLs), and introduces an adaptive sparse polynomial chaos expansion combining hyperbolic truncation scheme with orthogonal matching pursuit method (AS-PCE (OMP)). This method is used as the basis to realize the uncertainty quantification (UQ) of radiated susceptibility and global sensitivity analysis (GSA) of input variables to output variables. GSA considers the influencing factors of the incident field and transmission-line geometric parameters. The global sensitivity indices of each input variable are calculated for varying impedance loads. The accuracy and efficiency of the proposed method are verified compared with the results of the polynomial chaos expansion based least angle regression method and Monte Carlo methods.
Downloads
References
S. Arianos, M. A. Francavilla, M. Righero, F. Vipiana, P. Savi, S. Bertuol, M. Ridel, and J. Parmantier, “Evaluation of the modeling of an EM illumination on an aircraft cable harness,” IEEE Trans. Electromagn. Compat., vol. 56, no. 2, pp. 844-853, Apr. 2014.
Z. Fei, Y. Huang, J. Zhou, and C. Song, “Numerical analysis of a transmission line illuminated by a random plane-wave field using stochastic reduced order models,” IEEE Access, vol. 5, pp. 8741-8751, May 2017.
D. Bellan and S. Pignari, “A probabilistic model for the response of an electrically short two-conductor transmission line driven by a random plane wave field,” IEEE Trans. on Electromagn. Compat., vol. 43, no. 2, pp. 130-139, May 2001.
R. Trinchero, I. S. Stievano, and F. G. Canavero, “Black-box modeling of the maximum currents induced in harnesses during automotive radiated immunity tests,” IEEE Trans. Electromagn. Compat., vol. 62, no. 2, pp. 627-630, Apr. 2019.
A. Kouassi, J. Bourinet, S. Lalléchère, P. Bonnet, and M. Fogli, “Reliability and sensitivity analysis of transmission lines in a probabilistic EMC context,” IEEE Trans. Electromagn. Compat., vol. 58, no. 2, pp. 561-572, Apr. 2016.
H. Karami, A. Mostajabi, M. Azadifar, M. Rubinstein, C. Zhuang, and F. Rachidi, “Machine learning-based lightning localization algorithm using lightning-induced voltages on transmission lines,” IEEE Trans. Electromagn. Compat., vol. 62, no. 6, pp. 2512-2519, Dec. 2020.
S. De Ridder, D. Spina, N. Toscani, F. Grassi, D. V. Ginste, and T. Dhaene, “Machine-learning-based hybrid random-fuzzy uncertainty quantification for EMC and SI assessment,” IEEE Trans. Electromagn. Compat., vol. 62, no. 6, pp. 2538-2546, Dec. 2020.
T. Wang, W. Yan, L. Wang, and G. Zhang, “Uncertainty analysis of random field coupling to Stochastic cables,” Shenzhen, China, APEMC. IEEE, pp. 17-21, May 2016
P. Manfredi and F. G. Canavero, “Polynomial chaos for random field coupling to transmission lines,” IEEE Trans. Electromagn Compat., vol. 54, no. 3, pp. 677-680, Jun. 2012.
M. Larbi, I. S. Stievano, F. G. Canavero, and P. Besnier, “Variability impact of many design parameters: the case of a realistic electronic link,” IEEE Trans. Electromagn. Compat., vol. 60, no. 1, pp. 34-41, Jul. 2017.
Q. Yu, W. Liu, K. Yang, X. Ma, and T. Wang, “Uncertainty quantification of the crosstalk in multiconductor transmission lines via degree adaptive stochastic response surface method,” Applied Computational Electromagnetics Society (ACES) Journal, vol. 36, no. 2, pp. 174-183, Feb. 2021.
T. Wang, Q. Yu, X. Li, G. Le, and H. Zhao, “Radiated susceptibility analysis of multiconductor transmission lines based on polynomial chaos,” Applied Computational Electromagnetics Society (ACES) Journal, vol. 35, no. 12, pp. 1556-1566, Dec. 2020.
T. Bdour and A. Reineix, “Global sensitivity analysis and uncertainty quantification of radiated susceptibility in PCB using nonintrusive polynomial chaos expansions,” IEEE Trans. Electromagn. Compat., vol. 58. no. 3, pp. 939-942, Jun. 2016.
C. R. Paul, Analysis of Multiconductor Transmission Lines, 2nd ed. New York, NY, USA: Wiley, 2008.
D. Xiu and G. E. Karniadakis, “Modeling uncertainty in flow simulations via generalized polynomial chaos,” J. Comput. Phys., vol. 187, no. 1, pp. 137-167, Oct. 2003.
R. Mukerjee and C. F. J. Wu, A Modern Theory of Factorial Designs, New York: Springer, 2006.
I. M. Sobol, “Sensitivity estimates for nonlinear mathematical models,” Math. Model. Comput. Exp., vol. 1, no. 1, pp. 112-118, Jan. 1993.
M. Larbi, I. S. Stievano, F. G. Canavero, and P. Besnier, “Identification of main factors of uncertainty in a microstrip line network,” Prog. Electromagn. Res., vol. 162, pp. 61-72. Jan. 2018.
