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Stochastic Collocation Applications in Computational Electromagnetics

Author

Listed:
  • Dragan Poljak
  • Silvestar Šesnić
  • Mario Cvetković
  • Anna Šušnjara
  • Hrvoje Dodig
  • Sébastien Lalléchère
  • Khalil El Khamlichi Drissi

Abstract

The paper reviews the application of deterministic-stochastic models in some areas of computational electromagnetics. Namely, in certain problems there is an uncertainty in the input data set as some properties of a system are partly or entirely unknown. Thus, a simple stochastic collocation (SC) method is used to determine relevant statistics about given responses. The SC approach also provides the assessment of related confidence intervals in the set of calculated numerical results. The expansion of statistical output in terms of mean and variance over a polynomial basis, via SC method, is shown to be robust and efficient approach providing a satisfactory convergence rate. This review paper provides certain computational examples from the previous work by the authors illustrating successful application of SC technique in the areas of ground penetrating radar (GPR), human exposure to electromagnetic fields, and buried lines and grounding systems.

Suggested Citation

  • Dragan Poljak & Silvestar Šesnić & Mario Cvetković & Anna Šušnjara & Hrvoje Dodig & Sébastien Lalléchère & Khalil El Khamlichi Drissi, 2018. "Stochastic Collocation Applications in Computational Electromagnetics," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-13, May.
  • Handle: RePEc:hin:jnlmpe:1917439
    DOI: 10.1155/2018/1917439
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    Cited by:

    1. Abdumauvlen Berdyshev & Dossan Baigereyev & Kulzhamila Boranbek, 2023. "Numerical Method for Fractional-Order Generalization of the Stochastic Stokes–Darcy Model," Mathematics, MDPI, vol. 11(17), pages 1-27, September.

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