Publication detail

Variance-based Sensitivity Indices for Stochastic Models with Correlated Inputs

KALA, Z.

Original Title

Variance-based Sensitivity Indices for Stochastic Models with Correlated Inputs

Type

conference paper

Language

English

Original Abstract

The goal of this article is the formulation of the principles of one of the possible strategies in implementing correlation between input random variables so as to be usable for algorithm development and the evaluation of Sobol’s sensitivity analysis. With regard to the types of stochastic computational models, which are commonly found in structural mechanics, an algorithm was designed for effective use in conjunction with Monte Carlo methods. Sensitivity indices are evaluated for all possible permutations of the decorrelation procedures for input parameters. The evaluation of Sobol’s sensitivity coefficients is illustrated on an example in which a computational model was used for the analysis of the resistance of a steel bar in tension with statistically dependent input geometric characteristics.

Keywords

Steel, Sensitivity, Structures, Reliability, Simulation, Random, Stochastic, Correlation

Authors

KALA, Z.

RIV year

2015

Released

1. 3. 2015

ISBN

978-0-7354-1287-3

Book

Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014

Pages from

1

Pages to

4

Pages count

4

URL

http://dx.doi.org/10.1063/1.4913077

BibTex

@inproceedings{BUT114238,
  author="Zdeněk {Kala}",
  title="Variance-based Sensitivity Indices for Stochastic Models with Correlated Inputs",
  booktitle="Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014",
  year="2015",
  pages="1--4",
  doi="10.1063/1.4913077",
  isbn="978-0-7354-1287-3",
  url="http://dx.doi.org/10.1063/1.4913077"
}