Publication detail

Identification of Stochastic Interactions in Nonlinear Models of Structural Mechanics

KALA, Z.

Original Title

Identification of Stochastic Interactions in Nonlinear Models of Structural Mechanics

English Title

Identification of Stochastic Interactions in Nonlinear Models of Structural Mechanics

Type

conference paper

Language

en

Original Abstract

In the paper, the polynomial approximation is presented by which the Sobol sensitivity analysis can be evaluated with all sensitivity indices. The nonlinear FEM model is approximated. The input area is mapped using simulations runs of Latin Hypercube Sampling method. The domain of the approximation polynomial is chosen so that it were possible to apply large number of simulation runs of Latin Hypercube Sampling method. The method presented also makes possible to evaluate higher-order sensitivity indices, which could not be identified in case of nonlinear FEM.

English abstract

In the paper, the polynomial approximation is presented by which the Sobol sensitivity analysis can be evaluated with all sensitivity indices. The nonlinear FEM model is approximated. The input area is mapped using simulations runs of Latin Hypercube Sampling method. The domain of the approximation polynomial is chosen so that it were possible to apply large number of simulation runs of Latin Hypercube Sampling method. The method presented also makes possible to evaluate higher-order sensitivity indices, which could not be identified in case of nonlinear FEM.

Keywords

Steel, Strut, Buckling, Structure, Sensitivity, Structural Mechanics, Statistics

Released

01.01.2017

Location

Řecko

ISBN

978-0-7354-1538-6

Book

AIP Conference Proceedings

Pages from

1

Pages to

4

Pages count

4

Documents

BibTex


@inproceedings{BUT145986,
  author="Zdeněk {Kala}",
  title="Identification of Stochastic Interactions in Nonlinear Models of Structural Mechanics",
  annote="In the paper, the polynomial approximation is presented by which the Sobol sensitivity analysis can be evaluated with all sensitivity indices. The nonlinear FEM model is approximated. The input area is mapped using simulations runs of Latin Hypercube Sampling method. The domain of the approximation polynomial is chosen so that it were possible to apply large number of simulation runs of Latin Hypercube Sampling method. The method presented also makes possible to evaluate higher-order sensitivity indices, which could not be identified in case of nonlinear FEM.",
  booktitle="AIP Conference Proceedings",
  chapter="145986",
  doi="10.1063/1.4992640",
  howpublished="online",
  number="1863",
  year="2017",
  month="january",
  pages="1--4",
  type="conference paper"
}