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Title:Stochastic modeling in computational electromagnetics
Author(s):Ochoa Munoz, Juan
Director of Research:Cangellaris, Andreas C.
Doctoral Committee Chair(s):Cangellaris, Andreas C.
Doctoral Committee Member(s):Chew, Weng Cho; Raginsky, Maxim; Schutt-Ainé, José E.
Department / Program:Electrical & Computer Eng
Discipline:Electrical & Computer Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Stochastic modeling
Stochastic collocation
Computaional electromagnetics
Yield estimation
Dimensionality reduction
Monte Carlo
Stochastic macromodeling
Signal integrity
Disordered periodic waveguides
Random scattering
Abstract:This thesis presents methodologies for the efficient assessment of the impact of statistical variability on the performance of electromagnetic structures and systems. The proposed techniques are based on the Sparse Grid Collocation method which is a more efficient alternative than the standard Monte Carlo method. The high dimensionality challenge associated with certain stochastic problems, defined in terms of correlated random variables, is alleviated with a random-space dimensionality reduction technique that, in combination with an a-priori sensitivity assessment, results in an accurate technique for the statistical characterization and yield estimation of stochastic electromagnetic systems. Two real-world applications demonstrate the benefits of the proposed methodologies, a pair of interconnects with random cross sectional parameters, and a band pass microwave filter with randomly positioned loads. The thesis focuses on methodologies for the assessment of structures exhibiting localized uncertainty, namely random changes in the geometric and material properties occurring throughout the structure under consideration. Among the proposed methodologies, a technique is developed for the stochastic electromagnetic macromodeling of two-dimensional subdomains exhibiting geometric and material uncertainty. The methodology makes use of the theory of polynomial chaos expansion and the concept of a global impedance/admittance matrix relationship defined over a circular surface enclosing the cross-sectional geometry of the domain of interest to construct a stochastic global impedance/admittance matrix boundary condition on the surrounding surface. Such a method is generalized for the broadband response of the random domains through a stochastic model order reduction technique based on the Krylov subspace projection. Numerical examples are used to demonstrate the attributes of the proposed stochastic macromodel to the solution of electromagnetic scattering problems by an ensemble of targets exhibiting uncertainty. Macromodeling is also employed for the assessment of signal integrity performance in high-speed interconnect structures exhibiting localized uncertainty. Specifically, two applications are studied for demonstrative purposes, the first one concerns a coaxial cable with a random permittivity profile and the second one, a multiconducting interconnect structure with variability in its routing. In the first case, an effective stochastic homogeneous model of the dielectric permittivity is constructed that is used to quantify the induced distortion of the transmitted signal in terms of a random jitter. In the second signal-integrity application, a methodology based on a passive parametric macromodeling technique is developed for the predictive analysis of the impact of interconnect routing uncertainty on their transmission properties. The last stochastic application presents an expedient methodology for the predictive analysis of the impact of statistical disorder on the electromagnetic attributes of periodic waveguides. The proposed methodology makes use of ideas from the Anderson localization theory to derive closed-form expressions for the calculation of an effective exponential decay ratio that quantifies the impact of periodicity disorder on the transmission properties of the wave-guide. The computational efficiency of the proposed method over Monte Carlo based alternatives is demonstrated through a specific example involving a periodically-loaded parallel plate waveguide.
Issue Date:2014-01-16
URI:http://hdl.handle.net/2142/46581
Rights Information:Copyright 2013 Juan Ochoa Munoz
Date Available in IDEALS:2014-01-16
Date Deposited:2013-12


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