A Fast Polynomial Chaos Expansion for Uncertainty Quantification in Stochastic Electromagnetic Problems

Variations in material properties, boundary conditions, or the geometry can be expected in most electromagnetic problems. When these uncertainties in different regions of the model space are considered simultaneously, the stochastic dimensionality and the computational cost increase. Hence, uncertainty quantification in such problems is seldom attempted even though its quantification leads to a robust model. In this letter, a nonintrusive least square polynomial chaos expansion method is employed to quantify uncertainty due to stochastic variation of material properties. Using this method, the deviation from the mean performance for the transmission coefficient is obtained across the operational frequency range. The results compare well with Monte Carlo method and require just 1% of its total computational time.