2026-09-21T13:49:22Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/117839 2023-07-11 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Chen, Xu 2022-12 application/pdf en text Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms The student, Xingjian Shangguan, accepted the attached license on 2022-12-06 at 15:05. The student, Xingjian Shangguan, submitted this Thesis for approval on 2022-12-06 at 20:52. This Thesis was approved for publication on 2022-12-09 at 11:27. DSpace SAF Submission Ingestion Package generated from Vireo submission #18761 on 2023-04-12 at 07:38:52 Polynomial-based surrogate models for uncertainty quantification of passive electronic systems Shangguan, Xingjian 2022-12-09 Polynomial Chaos Rational Polynomial Chaos Uncertainty Quantification Surrogate Model Electronics Packaging Principal Component Analysis. 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. Thesis eng https://hdl.handle.net/2142/117839 Copyright 2022 Xingjian Shangguan M.S. Thesis Electrical & Computer Engr University of Illinois at Urbana-Champaign Electrical & Computer Eng