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Hybrid Possibilistic-Probabilistic Approach to Uncertainty Quantification in Electromagnetic Compatibility Models

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Uncertainty Modeling for Engineering Applications

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Abstract

In this Chapter, possibility theory is briefly presented as a framework to deal with electromagnetic compatibility (EMC) problems characterized by incomplete or lack of knowledge (i.e., epistemic uncertainty) on the variability of some of the involved parameters. Accordingly, such parameters are modeled by fuzzy variables (characterized by possibility distributions), that, in real-case scenarios, usually coexist with random variables (characterized by probability distributions). This is the case of typical test setups for EMC verification, such as the radiated susceptibility case study here presented, where the uncertainty of output quantities strongly depends on some input parameters, whose probability distribution functions are unknown. To overcome this limitation, a hybrid approach is presented to propagate the uncertainty within the model, still retaining the possibilistic and probabilistic nature of the two sets of involved parameters. Two methods to aggregate the obtained random-fuzzy sets are presented and compared versus the results obtained by running fully-probabilistic Monte Carlo (MC) simulations, where all uncertain parameters were assigned known probability distributions.

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References

  1. Paladian F, Bonnet P, Lallechere S (2011) Modeling complex systems for EMC applications by considering uncertainties. In: Proceedings 30th URSI general assembly and scientific symposium, Istanbul, Turkey, 13–20 Aug 2011, p 14

    Google Scholar 

  2. Pham TA, Gad E, Nakhla MS, Achar R (2014) Decoupled polynomial chaos and its applications to statistical analysis of high-speed interconnects. IEEE Trans Compon Packag Manuf Technol 4(10):1634–1647

    Article  Google Scholar 

  3. Manfredi P, Vande Ginste D, Stievano IS, De Zutter D, Canavero FG (2017) Stochastic transmission line analysis via polynomial chaos methods: an overview. IEEE Electromagn Compat Mag 6(3):77–84

    Article  Google Scholar 

  4. Fei Z, Huang Y, Zhou J, Xu Q (2017) Uncertainty quantification of crosstalk using stochastic reduced order models. IEEE Trans Electromagn Compat 59(1):228–239

    Article  Google Scholar 

  5. Grassi F, Spadacini G, Pignari SA (2013) The concept of weak imbalance and its role in the emissions and immunity of differential lines. IEEE Trans Electromagn Compat 55(6):1346–1349

    Article  Google Scholar 

  6. Spadacini G, Grassi F, Pignari SA (2015) Field-to-wire coupling model for the common mode in random bundles of twisted-wire pairs. IEEE Trans Electromagn Compat 57(5):1246–1254

    Article  Google Scholar 

  7. Li Y, Chen J, Feng L (2013) Dealing with uncertainty: a survey of theories and practices. IEEE Trans Knowl Data Eng 25(11):2463–2482

    Article  Google Scholar 

  8. Prasad AK, Roy S (2017) A novel dimension fusion based polynomial chaos approach for mixed aleatory-epistemic uncertainty quantification of carbon nanotube interconnects. In: Proceedings of the IEEE international symposium on electromagnetic compatibility and signal/power integrity, Washington, DC, 7–11 Aug 2017, pp 108–111

    Google Scholar 

  9. Guyonnet D, Bourgine B, Dubois D, Fargier H, Cme B, Chils JP (2003) Hybrid approach for addressing uncertainty in risk assessments. J Environ Eng 129:68–78

    Article  Google Scholar 

  10. Baraldi P, Popescu IC, Zio E (2008) Predicting the time to failure of a randomly degrading component by a hybrid Monte Carlo and possibilistic method. In: Proceedings of the 2008 international conference on prognostics and health management, Denver, CO, pp 1–8

    Google Scholar 

  11. Salicone S (2007) Measurement uncertainty: an approach via the mathematical theory of evidence. Springer

    Google Scholar 

  12. Shafer G (1976) A mathematical theory of evidence. Princeton University Press, Princeton, NJ, USA

    MATH  Google Scholar 

  13. Dubois D, Prade H (1992) When upper probabilities are possibility measures. Fuzzy Sets Syst 49:65–74

    Article  MathSciNet  Google Scholar 

  14. Zadeh LA (1999) Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst 100:9–34

    Article  Google Scholar 

  15. Baudrit C, Dubois D, Guyonnet D (2006) Joint propagation and exploitation of probabilistic and possibilistic information in risk assessment. IEEE Trans Fuzzy Syst 14(5):593–608

    Article  Google Scholar 

  16. Dubois D, Foulloy L, Mauris G, Prade H (2004) Probability-possibility transformations, triangular fuzzy sets, and probabilistic inequalities. Reliable Comput 10(4):273–297

    Article  MathSciNet  Google Scholar 

  17. Baudrit C, Dubois D, Guyonnet D (2005) Post-processing the hybrid method for addressing uncertainty in risk assessment. J Environ Eng 131(12):1750–1754

    Article  Google Scholar 

  18. CISPR 25 (2008) Radio disturbance characteristics for the protection of receivers used on board vehicles, boats, and on devices-limits and methods of measurement, 3rd ed

    Google Scholar 

  19. ISO-11452 (2011) Road vehicles-component test methods for electrical disturbances from narrowband radiated electromagnetic energy-Part 2: Absorber-lined shielded enclosure, 2nd ed, 01 Nov 2011

    Google Scholar 

  20. RTCA-EUROCAE (2007) Environmental conditions and test procedures for airborne equipment, Section 20: radio frequency susceptibility (radiated and conducted), RTCA DO-160F, 6 Dec 2007

    Google Scholar 

  21. Department of Defense Interface Standard (1999) Requirements for the control of electromagnetic interference characteristics of subsystems and equipment, MIL-STD-461E, 20 Aug 1999

    Google Scholar 

  22. Pignari SA, Spadacini G (2011) Plane-wave coupling to a twisted-wire pair above ground. IEEE Trans Electromagn Compat 53(2):508–523

    Article  Google Scholar 

  23. Spadacini G, Grassi F, Pignari SA (2013) On the combined effect of random nonuniformity and deformation of twisting on the radiated immunity of twisted-wire pairs. In: Proceedings of the 2013 IEEE international symposium on on EMC, Denver, CO, USA, 5–9 Aug 2013, pp 489–493

    Google Scholar 

  24. Badini L, Toscani N, Spadacini G, Grassi F, Pignari SA (2017) A possibilistic approach to radiated susceptibility of twisted-wire pairs. In: Proceedings of the IEEE international symposium on electromagnetic compatibility and signal/power integrity, Washington, DC, 7–11 Aug 2017, pp 96–101

    Google Scholar 

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Authors and Affiliations

  1. Department of Electronics, Information and Bioengineering, Politecnico di Milano, P.za L. da Vinci, 32, 20133, Milano, Italy

    Nicola Toscani, Flavia Grassi, Giordano Spadacini & Sergio A. Pignari

Authors
  1. Nicola Toscani
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  2. Flavia Grassi
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  3. Giordano Spadacini
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  4. Sergio A. Pignari
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Corresponding author

Correspondence to Flavia Grassi .

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Editors and Affiliations

  1. Department of Electronics and Telecommunications (DET), Politecnico di Torino, Turin, Italy

    Flavio Canavero

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Toscani, N., Grassi, F., Spadacini, G., Pignari, S.A. (2019). Hybrid Possibilistic-Probabilistic Approach to Uncertainty Quantification in Electromagnetic Compatibility Models. In: Canavero, F. (eds) Uncertainty Modeling for Engineering Applications. PoliTO Springer Series. Springer, Cham. https://doi.org/10.1007/978-3-030-04870-9_10

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