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"
}