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Abstract-Stochastic spectral methods can generate accurate compact stochastic models for electromagnetic problems with material and geometric uncertainties. This letter presents an improved implementation of the maximum-entropy algorithm to compute the density function of an obtained generalized polynomial chaos expansion in Magnetic Resonance Imaging (MRI) applications. Instead of using statistical moments, we show that the expectations of some orthonormal polynomials can be better constraints for the optimization flow. The proposed algorithm is coupled with a finite element-boundary element method (FEM-BEM) domain decomposition field solver to obtain a robust computational prototyping for MRI problems with low and high dimensional uncertainties.

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A finite element and combined field integral equation domain decomposition approach is presented for electromagnetic scattering from multiple domains. The main computational bottleneck is the construction of the dense coupling impedance matrix blocks capturing the interactions between different domains. In order to accelerate such coupling computation, A. Hochman et al. in [1] proposed the combination of the randomized singular value decomposition (rSVD) and of the discrete empirical interpolation method (DEIM). The computation of the incident fields due to equivalent currents on each domain is reduced to just a few observation points that can be located optimally and automatically by the DEIM algorithm. Furthermore, the compressed form of the coupling blocks generated by that approach significantly reduces the memory requirement and computational cost associated with the iterative solution of the global system matrix. In this paper, we focus on developing an implementation of such approach for a domain decomposition solver that combines finite element method (FEM) with boundary element method (BEM). Results on a simplified magnetic resonance imaging (MRI) scattering on human body are finally presented to validate our code implementation.Index Terms-multi-solver domain decomposition method (MS-DDM); MRI scattering; discrete empirical interpolation method (DEIM); proper orthogonal decomposition (POD).

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A precipitator section is modeled numerically in 3D to determine the collection efficiency for conductive diesel exhaust particulates. It consists of a circular tube and a wire electrode mounted at the center of the tube, supplied with a negative high dc voltage, while the tube is electrically grounded. The analytical solutions of Poisson and current continuity equations are implemented to obtain the ionic space charge density and electric potential distributions in the channel. Commercial CFD FLUENT software is used to solve the k-e turbulent flow model, while also considering the electrical body forces. Particle charging and motion equations are solved using Discrete Phase Model (DPM) feature of the FLUENT and programming User Defined Functions (UDFs). Particles are assumed to be charged by combined field and diffusion charging mechanisms. Effects of some electrical characteristics of diesel exhaust particulates, such as charge-to-mass ratio and particle migration velocity, on collection efficiency are assessed. Patterns of particle deposition along the channel are evaluated and compared for different particle sizes. Numerical modeling of the 3D EHD flow pattern induced by corona discharge is demonstrated in the cross section of the tube when the corona wire is slightly off-center (eccentric) in an arbitrary direction.