Publication detail

Failure Probability Estimation Using Asymptotic Sampling and Its Dependence upon the Selected Sampling Scheme

MARTINÁSKOVÁ, M. VOŘECHOVSKÝ, M.

Original Title

Failure Probability Estimation Using Asymptotic Sampling and Its Dependence upon the Selected Sampling Scheme

Type

journal article - other

Language

English

Original Abstract

The article examines the use of Asymptotic Sampling (AS) for the estimation of failure probability. The AS algorithm requires samples of multidimensional Gaussian random vectors, which may be obtained by many alternative means that influence the performance of the AS method. Several reliability problems (test functions) have been selected in order to test AS with various sampling schemes: (i) Monte Carlo designs; (ii) LHS designs optimized using the Periodic Audze-Eglājs (PAE) criterion; (iii) designs prepared using Sobol’ sequences. All results are compared with the exact failure probability value.

Keywords

Asymptotic Sampling, failure probability, quasi-Monte Carlo, LHS designs

Authors

MARTINÁSKOVÁ, M.; VOŘECHOVSKÝ, M.

Released

30. 12. 2017

Publisher

De Gruyter Open

Location

online

ISBN

1804-4824

Periodical

Transactions of the VŠB – Technical University of Ostrava, Civil Engineering Series

Year of study

17

Number

2

State

Czech Republic

Pages from

65

Pages to

72

Pages count

8

URL

BibTex

@article{BUT143553,
  author="Magdalena {Martinásková} and Miroslav {Vořechovský}",
  title="Failure Probability Estimation Using Asymptotic Sampling and Its Dependence upon the Selected Sampling Scheme",
  journal="Transactions of the VŠB – Technical University of Ostrava, Civil Engineering Series",
  year="2017",
  volume="17",
  number="2",
  pages="65--72",
  doi="10.1515/tvsb-2017-0029",
  issn="1804-4824",
  url="http://www.degruyter.com/view/j/tvsb.2017.17.issue-2/tvsb-2017-0029/tvsb-2017-0029.xml?format=INT"
}