Providing estimates of the uncertainty in results obtained by Computational Electromagnetic (CEM) simulations is essential when determining the acceptability of the results. The Monte Carlo method (MCM) has been previously used to quantify the uncertainty in CEM simulations. Other computationally efficient methods have been investigated more recently, such as the polynomial chaos method (PCM) and the method of moments (MoM). This paper introduces a novel implementation of the PCM and the MoM into the finite-difference time-domain method. The PCM and the MoM are found to be computationally more efficient than the MCM, but can provide poorer estimates of the uncertainty in resonant electromagnetic compatibility data. Index Terms-Computational electromagnetism, finitedifference time domain (FDTD), method of moments (MoM), Monte Carlo, polynomial chaos, uncertainty analysis.

The realization that we can no longer take reserves of fossil fuels for granted, allied to issues of industrial sustainability, pollution and climate change has reawakened an interest in increasing our use of plants as a source of both chemicals and materials. Whereas plant-derived biomass, fermentable sugars and oils are now well recognized as sources of energy and liquid fuels, the use of green feedstocks for large-scale platform and fine chemical production is increasingly high on the agenda of industries wanting to reduce their environmental footprint.