Detail publikace

Variance-based Sensitivity Indices for Stochastic Models with Correlated Inputs

KALA, Z.

Originální název

Variance-based Sensitivity Indices for Stochastic Models with Correlated Inputs

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

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

Autoři

KALA, Z.

Rok RIV

2015

Vydáno

1. 3. 2015

ISBN

978-0-7354-1287-3

Kniha

Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014

Strany od

1

Strany do

4

Strany počet

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"
}