University of Illinois Urbana-Champaign

Polynomial-based surrogate models for uncertainty quantification of passive electronic systems

Shangguan, Xingjian

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SHANGGUAN-THESIS-2022.pdf

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https://hdl.handle.net/2142/117839

Description

Title
Polynomial-based surrogate models for uncertainty quantification of passive electronic systems
Author(s)
Shangguan, Xingjian
Issue Date
2022-12-09
Director of Research (if dissertation) or Advisor (if thesis)
Chen, Xu
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
  • polynomial chaos
  • rational polynomial chaos
  • uncertainty quantification
  • surrogate model
  • electronics packaging
  • principal component analysis.
Abstract
In this thesis, the state of the art of polynomial-based surrogate models for uncertainty quantification is reviewed. Different aspects of the surrogate models, including order selection, choice of polynomial basis, quadrature rules and regression-based coefficient obtain process, compression rate of principle component analysis and its relation to the order truncation, as well as the sampling of the design space, are discussed and compared. A new algorithm for sampling and a common denominator rational polynomial chaos formulation are proposed. Numerical results on an analytical distributed circuit model, a differential via structure, and a fan-out package are provided to demonstrate the applicability of the polynomial-based methods to work with passive electronic systems and structures. The proposed sampling method improved the $L_{\infty}$ norm of the error compared to the simulation. And the common denominator formulation provides speed-up to the rational polynomial chaos. And finally, a conclusion and directions for future work are presented.
Graduation Semester
2022-12
Type of Resource
Thesis
Handle URL
https://hdl.handle.net/2142/117839
Copyright and License Information
Copyright 2022 Xingjian Shangguan

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Graduate Theses and Dissertations at Illinois