Uncertainty propagation in the SAR induced in the head using polynomial chaos decomposition

Fitting an experimental data model to evaluate the Specific Absorption Rate (SAR) induced in the head model over time of our Finite-Difference Time-Domain (FDTD) process may lead to intractable calculations. These difficulties are due to the large number of parameters, and the amount of available data. In order to overcome these difficulties, statistical process control concepts have been introduced to develop a metamodel technique which parameterizes the SAR and allows the analysis of the parameters that can have an influence on the head tissues exposure. The appropriate stochastic metamodel and the Polynomial Chaos (PC) expansion coefficients are estimated by least-square regression. The objective of this paper is to show that the metamodelling technique based on a polynomial chaos can be an efficient tool to simplify uncertainty propagation problem to estimate the SAR10g induced in the head and the SAR average over 1g of the brain.