engleski

Review of Deterministic-Stochastic Procedures in Electromagnetic-Thermal Dosimetry of The Realistic Human Head Model Exposed to Non-Ionizing Radiation

Computational models used in electromagnetic-thermal dosimetry suffer from drawbacks pertaining to the uncertainties in input data set resulting in the uncertainty propagation to the response of interest such as Specific Absorption Rate (SAR), or temperature increase due to the human exposure to non- ionizing radiation. Recently, deterministic-stochastic modelling is used to overcome these difficulties. Contrary to the traditional use of a robust Monte Carlo Method (MCM), with rather slow convergence rate, the Stochastic Collocation method (SCM) has been recently used due to its nonintrusive nature and the polynomial representation of the stochastic output, thus appreciably reducing the number of simulations. The present paper outlines some SCM applications in dosimetry previously reported by the authors. Thus, the realistic eye, brain and head model consisting of brain, skull and scalp exposed to a plane wave is considered and the related SAR induced in the head is determined as the dosimetry quantity of interest. Incident plane wave is treated as an exterior scattering problem formulated by the Stratton-Chu equation, and the interior domain is governed by the vector Helmholtz equation. Homogeneous brain model is formulated in terms of the coupled surface integral equations, numerically solved via Method of Moments (MoM). The corresponding temperature rise is obtained by solving the Pennes’ bioheat transfer equation. The governing equations of electromagnetic dosimetry are solved via the hybrid finite element/boundary element method (FEM/BEM) while the temperature distribution in the head is obtained by solving the bioheat equation via FEM.

dosimetry ; human exposure to EM fields ; electromagnetic-thermal dosimetry ; deterministic-stochastic dosimetry ; human head model

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