Abstract
The uncertainties present in a variety of electromagnetic (EM) problems may have important effects on the output parameters of interest. Unfortunately, deterministic schemes are not applicable in such cases, as they only utilize the nominal value of each random variable. In this work, a two-dimensional (2D) finite-difference time-domain (FDTD) algorithm is presented, which is suitable for assessing randomness in the electrical properties, as well as in the dimensions of orthogonal objects. The proposed technique is based on the stochastic FDTD method and manages to extract the mean and the standard deviation of the involved field quantities in one realization. This approach is applied to three test cases, where uncertainty exists in the electrical and geometrical parameters of various materials. The numerical results demonstrate the validity of our scheme, as similar outcomes are extracted compared to the Monte Carlo (MC) algorithm.
Highlights
Wave propagation in a material with random electric and geometric properties may introduce uncertainty in the involved field quantities
Deterministic analysis is not suitable in those cases, as it only takes into account the nominal values of each random variable
We introduce an extension of the S-finite-difference time-domain (FDTD) technique, which is able to assess random media, as well as uncertainties in the dimensions of rectangular dielectrics
Summary
Wave propagation in a material with random electric and geometric properties may introduce uncertainty in the involved field quantities. A reliable assessment of such randomness is an essential step, since neglecting the latter may increase the risk of misinterpretation of the simulated outcomes. Deterministic analysis is not suitable in those cases, as it only takes into account the nominal values of each random variable. For this reason, several methods exist in the literature for solving stochastic electromagnetic (EM) problems. The most common technique for uncertainty assessment is the Monte Carlo (MC) algorithm [3]
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