An ME-PC Enhanced HDMR Method for Efficient Statistical Analysis of Multiconductor Transmission Line Networks

Handle URI:
http://hdl.handle.net/10754/552901
Title:
An ME-PC Enhanced HDMR Method for Efficient Statistical Analysis of Multiconductor Transmission Line Networks
Authors:
Yucel, Abdulkadir C.; Bagci, Hakan ( 0000-0003-3867-5786 ) ; Michielssen, Eric
Abstract:
An efficient method for statistically characterizing multiconductor transmission line (MTL) networks subject to a large number of manufacturing uncertainties is presented. The proposed method achieves its efficiency by leveraging a high-dimensional model representation (HDMR) technique that approximates observables (quantities of interest in MTL networks, such as voltages/currents on mission-critical circuits) in terms of iteratively constructed component functions of only the most significant random variables (parameters that characterize the uncertainties in MTL networks, such as conductor locations and widths, and lumped element values). The efficiency of the proposed scheme is further increased using a multielement probabilistic collocation (ME-PC) method to compute the component functions of the HDMR. The ME-PC method makes use of generalized polynomial chaos (gPC) expansions to approximate the component functions, where the expansion coefficients are expressed in terms of integrals of the observable over the random domain. These integrals are numerically evaluated and the observable values at the quadrature/collocation points are computed using a fast deterministic simulator. The proposed method is capable of producing accurate statistical information pertinent to an observable that is rapidly varying across a high-dimensional random domain at a computational cost that is significantly lower than that of gPC or Monte Carlo methods. The applicability, efficiency, and accuracy of the method are demonstrated via statistical characterization of frequency-domain voltages in parallel wire, interconnect, and antenna corporate feed networks.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
An ME-PC Enhanced HDMR Method for Efficient Statistical Analysis of Multiconductor Transmission Line Networks 2015:1 IEEE Transactions on Components, Packaging and Manufacturing Technology
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Transactions on Components, Packaging and Manufacturing Technology
Issue Date:
5-May-2015
DOI:
10.1109/TCPMT.2015.2424679
Type:
Article
ISSN:
2156-3950; 2156-3985
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7101849
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorYucel, Abdulkadir C.en
dc.contributor.authorBagci, Hakanen
dc.contributor.authorMichielssen, Ericen
dc.date.accessioned2015-05-14T18:29:01Zen
dc.date.available2015-05-14T18:29:01Zen
dc.date.issued2015-05-05en
dc.identifier.citationAn ME-PC Enhanced HDMR Method for Efficient Statistical Analysis of Multiconductor Transmission Line Networks 2015:1 IEEE Transactions on Components, Packaging and Manufacturing Technologyen
dc.identifier.issn2156-3950en
dc.identifier.issn2156-3985en
dc.identifier.doi10.1109/TCPMT.2015.2424679en
dc.identifier.urihttp://hdl.handle.net/10754/552901en
dc.description.abstractAn efficient method for statistically characterizing multiconductor transmission line (MTL) networks subject to a large number of manufacturing uncertainties is presented. The proposed method achieves its efficiency by leveraging a high-dimensional model representation (HDMR) technique that approximates observables (quantities of interest in MTL networks, such as voltages/currents on mission-critical circuits) in terms of iteratively constructed component functions of only the most significant random variables (parameters that characterize the uncertainties in MTL networks, such as conductor locations and widths, and lumped element values). The efficiency of the proposed scheme is further increased using a multielement probabilistic collocation (ME-PC) method to compute the component functions of the HDMR. The ME-PC method makes use of generalized polynomial chaos (gPC) expansions to approximate the component functions, where the expansion coefficients are expressed in terms of integrals of the observable over the random domain. These integrals are numerically evaluated and the observable values at the quadrature/collocation points are computed using a fast deterministic simulator. The proposed method is capable of producing accurate statistical information pertinent to an observable that is rapidly varying across a high-dimensional random domain at a computational cost that is significantly lower than that of gPC or Monte Carlo methods. The applicability, efficiency, and accuracy of the method are demonstrated via statistical characterization of frequency-domain voltages in parallel wire, interconnect, and antenna corporate feed networks.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7101849en
dc.rights(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.subjectCrosstalken
dc.subjectgeneralized polynomial chaos (gPC)en
dc.subjectglobal sensitivity analysisen
dc.subjecthigh-dimensional model representation (HDMR)en
dc.subjectinterconnectsen
dc.subjectmulticonductor transmission lines (MTLs)en
dc.subjectmultielement probabilistic collocation (ME-PC) methoden
dc.subjectstochastic analysisen
dc.subjectsurrogate modelen
dc.subjecttolerance analysisen
dc.subjectuncertainty quantificationen
dc.titleAn ME-PC Enhanced HDMR Method for Efficient Statistical Analysis of Multiconductor Transmission Line Networksen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalIEEE Transactions on Components, Packaging and Manufacturing Technologyen
dc.eprint.versionPost-printen
dc.contributor.institutionDepartment of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109 USAen
kaust.authorBagci, Hakanen
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