Uncertainty Quantification for Electromagnetic Analysis via Efficient Collocation Methods.

[摘要] Electromagnetic (EM) devices and systems often are fraught by uncertainty in their geometry, configuration, and excitation. These uncertainties (often termed ;;random variables”) strongly and nonlinearly impact voltages and currents on mission-critical circuits or receivers (often termed ;;observables”). To ensure the functionality of such circuits or receivers, this dependency should be statistically characterized.In this thesis, efficient collocation methods for uncertainty quantification in EM analysis are presented. First, a Stroud-based stochastic collocation method is introduced to statistically characterize electromagnetic compatibility and interference (EMC/EMI) phenomena on electrically large and complex platforms. Second, a multi-element probabilistic collocation (ME-PC) method suitable for characterizing rapidly varying and/or discontinuous observables is presented. Its applications to the statistical characterization of EMC/EMI phenomena on electrically and complex platforms and transverse magnetic wave propagation in complex mine environments are demonstrated. In addition, the ME-PC method is applied to the statistical characterization of EM wave propagation in complex mine environments with the aid of a novel fast multipole method and fast Fourier transform-accelerated surface integral equation solver -- the first-ever full-wave solver capable of characterizing EM wave propagation in hundreds of wavelengths long mine tunnels. Finally, an iterative high-dimensional model representation technique is proposed to statistically characterize EMC/EMI observables that involve a large number of random variables. The application of this technique to the genetic algorithm based optimization of EM devices is presented as well.

[发布机构] University of Michigan

[效力级别] Electromagnetic Compatibility and Interference Analysis

[关键词] Uncertainty Quantification;Electromagnetic Compatibility and Interference Analysis;Wireless Channel Characterization;Stochastic/Probabilistic Collocation Methods;Multi Element Probabilistic Collocation Method;High Dimensional Model Representation Technique;Electrical Engineering;Engineering;Electrical Engineering