Identification of composite uncertain material parameters from experimental modal data

K. Sepahvand, S. Marburg

Research output: Contribution to journalArticlepeer-review

51 Scopus citations

Abstract

Stochastic analysis of structures using probability methods requires the statistical knowledge of uncertain material parameters. This is often quite easier to identify these statistics indirectly from structure response by solving an inverse stochastic problem. In this paper, a robust and efficient inverse stochastic method based on the non-sampling generalized polynomial chaos method is presented for identifying uncertain elastic parameters from experimental modal data. A data set on natural frequencies is collected from experimental modal analysis for sample orthotropic plates. The Pearson model is used to identify the distribution functions of the measured natural frequencies. This realization is then employed to construct the random orthogonal basis for each vibration mode. The uncertain parameters are represented by polynomial chaos expansions with unknown coefficients and the same random orthogonal basis as the vibration modes. The coefficients are identified via a stochastic inverse problem. The results show good agreement with experimental data.

Original languageEnglish
Pages (from-to)148-153
Number of pages6
JournalProbabilistic Engineering Mechanics
Volume37
DOIs
StatePublished - 19 Aug 2014
Externally publishedYes

Keywords

  • Composite structures
  • Experimental modal analysis
  • Pearson model
  • Polynomial chaos
  • Uncertain parameter identification

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