Efficient stochastic EMC/EMI analysis using HDMR-generated surrogate models

Handle URI:
http://hdl.handle.net/10754/564410
Title:
Efficient stochastic EMC/EMI analysis using HDMR-generated surrogate models
Authors:
Yücel, Abdulkadir C.; Bagci, Hakan ( 0000-0003-3867-5786 ) ; Michielssen, Eric
Abstract:
Stochastic methods have been used extensively to quantify effects due to uncertainty in system parameters (e.g. material, geometrical, and electrical constants) and/or excitation on observables pertinent to electromagnetic compatibility and interference (EMC/EMI) analysis (e.g. voltages across mission-critical circuit elements) [1]. In recent years, stochastic collocation (SC) methods, especially those leveraging generalized polynomial chaos (gPC) expansions, have received significant attention [2, 3]. SC-gPC methods probe surrogate models (i.e. compact polynomial input-output representations) to statistically characterize observables. They are nonintrusive, that is they use existing deterministic simulators, and often cost only a fraction of direct Monte-Carlo (MC) methods. Unfortunately, SC-gPC-generated surrogate models often lack accuracy (i) when the number of uncertain/random system variables is large and/or (ii) when the observables exhibit rapid variations. © 2011 IEEE.
KAUST Department:
Physical Sciences and Engineering (PSE) Division; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Electrical Engineering Program; Computational Electromagnetics Laboratory
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2011 XXXth URSI General Assembly and Scientific Symposium
Conference/Event name:
2011 30th URSI General Assembly and Scientific Symposium, URSIGASS 2011
Issue Date:
Aug-2011
DOI:
10.1109/URSIGASS.2011.6050759
Type:
Conference Paper
ISBN:
9781424451173
Appears in Collections:
Conference Papers; Physical Sciences and Engineering (PSE) Division; Electrical Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorYücel, Abdulkadir C.en
dc.contributor.authorBagci, Hakanen
dc.contributor.authorMichielssen, Ericen
dc.date.accessioned2015-08-04T06:26:40Zen
dc.date.available2015-08-04T06:26:40Zen
dc.date.issued2011-08en
dc.identifier.isbn9781424451173en
dc.identifier.doi10.1109/URSIGASS.2011.6050759en
dc.identifier.urihttp://hdl.handle.net/10754/564410en
dc.description.abstractStochastic methods have been used extensively to quantify effects due to uncertainty in system parameters (e.g. material, geometrical, and electrical constants) and/or excitation on observables pertinent to electromagnetic compatibility and interference (EMC/EMI) analysis (e.g. voltages across mission-critical circuit elements) [1]. In recent years, stochastic collocation (SC) methods, especially those leveraging generalized polynomial chaos (gPC) expansions, have received significant attention [2, 3]. SC-gPC methods probe surrogate models (i.e. compact polynomial input-output representations) to statistically characterize observables. They are nonintrusive, that is they use existing deterministic simulators, and often cost only a fraction of direct Monte-Carlo (MC) methods. Unfortunately, SC-gPC-generated surrogate models often lack accuracy (i) when the number of uncertain/random system variables is large and/or (ii) when the observables exhibit rapid variations. © 2011 IEEE.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.titleEfficient stochastic EMC/EMI analysis using HDMR-generated surrogate modelsen
dc.typeConference Paperen
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentElectrical Engineering Programen
dc.contributor.departmentComputational Electromagnetics Laboratoryen
dc.identifier.journal2011 XXXth URSI General Assembly and Scientific Symposiumen
dc.conference.date13 August 2011 through 20 August 2011en
dc.conference.name2011 30th URSI General Assembly and Scientific Symposium, URSIGASS 2011en
dc.conference.locationIstanbulen
dc.contributor.institutionDepartment of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, United Statesen
kaust.authorBagci, Hakanen
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