Construction of polynomial chaos expansion for uncertain materail parameters from limited experimental data

K. Sepahvand, S. Marburg

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The knowledge of uncertain parameter distributions is often required to investigate any typical stochastic problem. It may be possible to directly measure some uncertain parameters but quite often is easier to identifying these parameters from system outputs via an inverse problem. In this paper, a robust and efficient method based of non-sampling technique, i.e. generalized polynomial chaos expansion, is presented to identifying the uncertain parameters from experimental modal data. We review the general polynomial chaos theory and relating issues for uncertain parameter identification. An application is presented for which samples of orthotropic plates are tested to measure the modal data. The distribution functions of uncertain parameters are derived from experimental eigen-frequencies via an inverse stochastic problem. The Pearson model is used to identify the type of density functions. This realization then is employed to construct random orthogonal basis for each uncertain parameter.

Original languageEnglish
Title of host publicationECCOMAS 2012 - European Congress on Computational Methods in Applied Sciences and Engineering, e-Book Full Papers
Pages1589-1604
Number of pages16
StatePublished - 2012
Externally publishedYes
Event6th European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2012 - Vienna, Austria
Duration: 10 Sep 201214 Sep 2012

Publication series

NameECCOMAS 2012 - European Congress on Computational Methods in Applied Sciences and Engineering, e-Book Full Papers

Conference

Conference6th European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2012
Country/TerritoryAustria
CityVienna
Period10/09/1214/09/12

Keywords

  • Parameter identification
  • Pearson model
  • Polynomial chaos
  • Uncertainty quantification

Fingerprint

Dive into the research topics of 'Construction of polynomial chaos expansion for uncertain materail parameters from limited experimental data'. Together they form a unique fingerprint.

Cite this