An adaptive multi-element probabilistic collocation method for statistical EMC/EMI characterization

Handle URI:
http://hdl.handle.net/10754/563131
Title:
An adaptive multi-element probabilistic collocation method for statistical EMC/EMI characterization
Authors:
Yücel, Abdulkadir C.; Bagci, Hakan ( 0000-0003-3867-5786 ) ; Michielssen, Eric
Abstract:
An adaptive multi-element probabilistic collocation (ME-PC) method for quantifying uncertainties in electromagnetic compatibility and interference phenomena involving electrically large, multi-scale, and complex platforms is presented. The method permits the efficient and accurate statistical characterization of observables (i.e., quantities of interest such as coupled voltages) that potentially vary rapidly and/or are discontinuous in the random variables (i.e., parameters that characterize uncertainty in a system's geometry, configuration, or excitation). The method achieves its efficiency and accuracy by recursively and adaptively dividing the domain of the random variables into subdomains using as a guide the decay rate of relative error in a polynomial chaos expansion of the observables. While constructing local polynomial expansions on each subdomain, a fast integral-equation-based deterministic field-cable-circuit simulator is used to compute the observable values at the collocation/integration points determined by the adaptive ME-PC scheme. The adaptive ME-PC scheme requires far fewer (computationally costly) deterministic simulations than traditional polynomial chaos collocation and Monte Carlo methods for computing averages, standard deviations, and probability density functions of rapidly varying observables. The efficiency and accuracy of the method are demonstrated via its applications to the statistical characterization of voltages in shielded/unshielded microwave amplifiers and magnetic fields induced on car tire pressure sensors. © 2013 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:
IEEE Transactions on Electromagnetic Compatibility
Issue Date:
Dec-2013
DOI:
10.1109/TEMC.2013.2265047
Type:
Article
ISSN:
00189375
Sponsors:
This work was supported by the National Science Foundation under Grant DMS 0713771, AFOSR/NSSEFF Program Award FA9550-10-1-0180, Sandia Grant "Development of Calderon Multiplicative Preconditioners with Method of Moments Algorithms," KAUST Grant 399813, ONR BRC Grant "Randomized Algorithms for Reduced Representations," and Center for Uncertainty Quantification in Computational Science and Engineering at KAUST.
Appears in Collections:
Articles; 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.accessioned2015-08-03T11:36:30Zen
dc.date.available2015-08-03T11:36:30Zen
dc.date.issued2013-12en
dc.identifier.issn00189375en
dc.identifier.doi10.1109/TEMC.2013.2265047en
dc.identifier.urihttp://hdl.handle.net/10754/563131en
dc.description.abstractAn adaptive multi-element probabilistic collocation (ME-PC) method for quantifying uncertainties in electromagnetic compatibility and interference phenomena involving electrically large, multi-scale, and complex platforms is presented. The method permits the efficient and accurate statistical characterization of observables (i.e., quantities of interest such as coupled voltages) that potentially vary rapidly and/or are discontinuous in the random variables (i.e., parameters that characterize uncertainty in a system's geometry, configuration, or excitation). The method achieves its efficiency and accuracy by recursively and adaptively dividing the domain of the random variables into subdomains using as a guide the decay rate of relative error in a polynomial chaos expansion of the observables. While constructing local polynomial expansions on each subdomain, a fast integral-equation-based deterministic field-cable-circuit simulator is used to compute the observable values at the collocation/integration points determined by the adaptive ME-PC scheme. The adaptive ME-PC scheme requires far fewer (computationally costly) deterministic simulations than traditional polynomial chaos collocation and Monte Carlo methods for computing averages, standard deviations, and probability density functions of rapidly varying observables. The efficiency and accuracy of the method are demonstrated via its applications to the statistical characterization of voltages in shielded/unshielded microwave amplifiers and magnetic fields induced on car tire pressure sensors. © 2013 IEEE.en
dc.description.sponsorshipThis work was supported by the National Science Foundation under Grant DMS 0713771, AFOSR/NSSEFF Program Award FA9550-10-1-0180, Sandia Grant "Development of Calderon Multiplicative Preconditioners with Method of Moments Algorithms," KAUST Grant 399813, ONR BRC Grant "Randomized Algorithms for Reduced Representations," and Center for Uncertainty Quantification in Computational Science and Engineering at KAUST.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectAdaptive algorithmen
dc.subjectElectromagnetic compatibility and interference (EMC/EMI)en
dc.subjectGeneralized polynomial chaos (gPC)en
dc.subjectMulti-dimensional integralen
dc.subjectMulti-element (ME)en
dc.subjectProbabilistic collocation (PC)en
dc.subjectSparse grid (SG)en
dc.subjectTensor product (TP)en
dc.subjectTolerance analysisen
dc.subjectUncertainty quantificationen
dc.titleAn adaptive multi-element probabilistic collocation method for statistical EMC/EMI characterizationen
dc.typeArticleen
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.journalIEEE Transactions on Electromagnetic Compatibilityen
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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