The method of separation for evolutionary spectral density estimation of multi-variate and multi-dimensional non-stationary stochastic processes

Handle URI:
http://hdl.handle.net/10754/599937
Title:
The method of separation for evolutionary spectral density estimation of multi-variate and multi-dimensional non-stationary stochastic processes
Authors:
Schillinger, Dominik; Stefanov, Dimitar; Stavrev, Atanas
Abstract:
The method of separation can be used as a non-parametric estimation technique, especially suitable for evolutionary spectral density functions of uniformly modulated and strongly narrow-band stochastic processes. The paper at hand provides a consistent derivation of method of separation based spectrum estimation for the general multi-variate and multi-dimensional case. The validity of the method is demonstrated by benchmark tests with uniformly modulated spectra, for which convergence to the analytical solution is demonstrated. The key advantage of the method of separation is the minimization of spectral dispersion due to optimum time- or space-frequency localization. This is illustrated by the calibration of multi-dimensional and multi-variate geometric imperfection models from strongly narrow-band measurements in I-beams and cylindrical shells. Finally, the application of the method of separation based estimates for the stochastic buckling analysis of the example structures is briefly discussed. © 2013 Elsevier Ltd.
Citation:
Schillinger D, Stefanov D, Stavrev A (2013) The method of separation for evolutionary spectral density estimation of multi-variate and multi-dimensional non-stationary stochastic processes. Probabilistic Engineering Mechanics 33: 58–78. Available: http://dx.doi.org/10.1016/j.probengmech.2013.01.005.
Publisher:
Elsevier BV
Journal:
Probabilistic Engineering Mechanics
KAUST Grant Number:
UK-c0020
Issue Date:
Jul-2013
DOI:
10.1016/j.probengmech.2013.01.005
Type:
Article
ISSN:
0266-8920
Sponsors:
This publication is partly based on work supported by Award no. UK-c0020, made by King Abdullah University of Science and Technology (KAUST). Furthermore, the authors acknowledge support from the Munich Center of Advanced Computing (MAC) and the International Graduate School of Science and Engineering (IGSSE) of the Technische Universität München. Extensive research reports related to buckling experiments in I-sections have been kindly provided by Prof. Kim Rasmussen from the University of Sydney and Dr. Andreas Lechner from the Technical University of Graz. Furthermore, Prof. Kai-Uwe Bletzinger and Michael Fischer from the Technische Universität München provided access to the research code Carat++ for benchmarking some of the Nastran results. Their assistance is also gratefully acknowledged.
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Full metadata record

DC FieldValue Language
dc.contributor.authorSchillinger, Dominiken
dc.contributor.authorStefanov, Dimitaren
dc.contributor.authorStavrev, Atanasen
dc.date.accessioned2016-02-28T06:32:50Zen
dc.date.available2016-02-28T06:32:50Zen
dc.date.issued2013-07en
dc.identifier.citationSchillinger D, Stefanov D, Stavrev A (2013) The method of separation for evolutionary spectral density estimation of multi-variate and multi-dimensional non-stationary stochastic processes. Probabilistic Engineering Mechanics 33: 58–78. Available: http://dx.doi.org/10.1016/j.probengmech.2013.01.005.en
dc.identifier.issn0266-8920en
dc.identifier.doi10.1016/j.probengmech.2013.01.005en
dc.identifier.urihttp://hdl.handle.net/10754/599937en
dc.description.abstractThe method of separation can be used as a non-parametric estimation technique, especially suitable for evolutionary spectral density functions of uniformly modulated and strongly narrow-band stochastic processes. The paper at hand provides a consistent derivation of method of separation based spectrum estimation for the general multi-variate and multi-dimensional case. The validity of the method is demonstrated by benchmark tests with uniformly modulated spectra, for which convergence to the analytical solution is demonstrated. The key advantage of the method of separation is the minimization of spectral dispersion due to optimum time- or space-frequency localization. This is illustrated by the calibration of multi-dimensional and multi-variate geometric imperfection models from strongly narrow-band measurements in I-beams and cylindrical shells. Finally, the application of the method of separation based estimates for the stochastic buckling analysis of the example structures is briefly discussed. © 2013 Elsevier Ltd.en
dc.description.sponsorshipThis publication is partly based on work supported by Award no. UK-c0020, made by King Abdullah University of Science and Technology (KAUST). Furthermore, the authors acknowledge support from the Munich Center of Advanced Computing (MAC) and the International Graduate School of Science and Engineering (IGSSE) of the Technische Universität München. Extensive research reports related to buckling experiments in I-sections have been kindly provided by Prof. Kim Rasmussen from the University of Sydney and Dr. Andreas Lechner from the Technical University of Graz. Furthermore, Prof. Kai-Uwe Bletzinger and Michael Fischer from the Technische Universität München provided access to the research code Carat++ for benchmarking some of the Nastran results. Their assistance is also gratefully acknowledged.en
dc.publisherElsevier BVen
dc.subjectEvolutionary power spectrum estimationen
dc.subjectMethod of separationen
dc.subjectNon-stationary stochastic processes and random fieldsen
dc.subjectSpectral representationen
dc.subjectStochastic buckling analysisen
dc.titleThe method of separation for evolutionary spectral density estimation of multi-variate and multi-dimensional non-stationary stochastic processesen
dc.typeArticleen
dc.identifier.journalProbabilistic Engineering Mechanicsen
dc.contributor.institutionTechnische Universitat Munchen, Munich, Germanyen
kaust.grant.numberUK-c0020en
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