Stochastic Collocation Applications in Computational Electromagnetics

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) me...

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Bibliographic Details
Published in:Mathematical problems in engineering 2018-01, Vol.2018 (2018), p.1-13
Main Authors: El Khamlichi Drissi, Khalil, Dodig, Hrvoje, Šušnjara, Anna, Cvetković, Mario, Šesnić, Silvestar, Poljak, Dragan, Lalléchère, Sébastien
Format: Article
Language:English
Subjects:
Antennas
Brain
Collocation
Computational electromagnetics
Confidence intervals
Dosimetry
Electromagnetic fields
Electromagnetism
Engineering
Engineering Sciences
Ground penetrating radar
Mathematical models
Methods
Microelectromechanical systems
Polynomials
Propagation
Robustness (mathematics)
Statistical analysis
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Summary: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.
ISSN:1024-123X
1563-5147
DOI:10.1155/2018/1917439