Techniques to increase computational efficiency in some deterministic and random electromagnetic propagation problems

• Main Author: Ozbayat, Selman
• Language: ENG
• Published: ScholarWorks@UMass Amherst 2013
• Subjects: Electrical engineering|Electromagnetics
• Online Access: https://scholarworks.umass.edu/dissertations/AAI3603130

Efficient computation in deterministic and uncertain electromagnetic propagation environments, tackled by parabolic equation methods, is the subject of interest of this dissertation. Our work is comprised of two parts. In the first part we determine efficient absorbing boundary conditions for propagation over deterministic terrain and in the second part we study techniques for efficient quantification of random parameters/outputs in volume and surface based electromagnetic problems. Domain truncation by transparent boundary conditions for open problems where parabolic equation is utilized to govern wave propagation are in general computationally costly. For the deterministic problem, we utilize two approximations to a convolution-in-space type discrete boundary condition to reduce the cost, while maintaining accuracy in far range solutions. Perfectly matched layer adapted to the Crank-Nicolson finite difference scheme is also verified for a 2-D model problem, where implemented results and stability analyses for different approaches are compared. For the random problem, efficient moment calculation of electromagnetic propagation/scattering in various propagation environments is demonstrated, where the dimensionality of the random space varies from N = 2 to N = 100. Sparse grid collocation methods are used to obtain expected values and distributions, as a non-intrusive sampling method. Due to the low convergence rate in the sparse grid methods for moderate dimensionality and above, two different adaptive strategies are utilized in the sparse grid construction. These strategies are implemented in three different problems. Two problems are concerned with uncertainty in propagation domain intrinsic parameters, whereas the other problem has uncertainty in the boundary shape of the terrain, which is realized as the perfectly conducting (PEC) Earth surface.