• DocumentCode
    104821
  • Title

    An Adaptive Multi-Element Probabilistic Collocation Method for Statistical EMC/EMI Characterization

  • Author

    Yucel, Abdulkadir C. ; Bagci, Hakan ; Michielssen, Eric

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA
  • Volume
    55
  • Issue
    6
  • fYear
    2013
  • fDate
    Dec. 2013
  • Firstpage
    1154
  • Lastpage
    1168
  • Abstract
    An adaptive multi-element probabilistic collocation (ME-PC) method for quantifying uncertainties in electromagnetic compatibility and interference phenomena involving electrically large, multi-scale, and complex platforms is presented. The method permits the efficient and accurate statistical characterization of observables (i.e., quantities of interest such as coupled voltages) that potentially vary rapidly and/or are discontinuous in the random variables (i.e., parameters that characterize uncertainty in a system´s geometry, configuration, or excitation). The method achieves its efficiency and accuracy by recursively and adaptively dividing the domain of the random variables into subdomains using as a guide the decay rate of relative error in a polynomial chaos expansion of the observables. While constructing local polynomial expansions on each subdomain, a fast integral-equation-based deterministic field-cable-circuit simulator is used to compute the observable values at the collocation/integration points determined by the adaptive ME-PC scheme. The adaptive ME-PC scheme requires far fewer (computationally costly) deterministic simulations than traditional polynomial chaos collocation and Monte Carlo methods for computing averages, standard deviations, and probability density functions of rapidly varying observables. The efficiency and accuracy of the method are demonstrated via its applications to the statistical characterization of voltages in shielded/unshielded microwave amplifiers and magnetic fields induced on car tire pressure sensors.
  • Keywords
    Monte Carlo methods; automobiles; cables (electric); electric field integral equations; electromagnetic compatibility; electromagnetic interference; magnetic field integral equations; magnetic shielding; microwave amplifiers; polynomials; pressure sensors; probability; random processes; statistical analysis; ME-PC method; Monte Carlo method; adaptive multielement probabilistic collocation method; car tire pressure sensor; electromagnetic compatibility; electromagnetic interference; fast integral-equation-based deterministic field-cable-circuit simulator; geometry; magnetic field; polynomial chaos collocation expansion; probability density function; random discontinuous variable; relative error decay rate; shielded-unshielded microwave amplifier; statistical EMC-EMI characterization; Adaptation models; Approximation methods; Computational modeling; Electromagnetic compatibility; Electromagnetic interference; Polynomials; Random variables; Adaptive algorithm; electromagnetic compatibility and interference (EMC/EMI); generalized polynomial chaos (gPC); multi-dimensional integral; multi-element (ME); probabilistic collocation (PC); sparse grid (SG); tensor product (TP); tolerance analysis; uncertainty quantification;
  • fLanguage
    English
  • Journal_Title
    Electromagnetic Compatibility, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9375
  • Type

    jour

  • DOI
    10.1109/TEMC.2013.2265047
  • Filename
    6531677