Structural reliability analysis on the basis of small samples

An interval quasi-Monte Carlo method

verfasst von

Hao Zhang, Hongzhe Dai, Michael Beer, Wei Wang

Abstract

In practice, reliability analysis of structures is often performed on the basis of limited data. Under this circumstance, there are practical difficulties in identifying unique distributions as input for a probabilistic analysis. But the selection of realistic probabilistic input is critical for the quality of the results of the reliability analysis. This problem can be addressed using an entire set of plausible distribution functions rather than one single distribution for random variables based on limited data. The uncertain nature of the available information is then reflected in the probabilistic input. An imprecise probability distribution can be modeled by a probability box, i.e., the bounds of the cumulative distribution function for the random variable. Sampling-based methods have been proposed to perform reliability analysis with probability boxes. However, direct sampling of probability boxes requires a large number of samples. The computational cost can be very high as each simulation involves an interval analysis (a range-finding problem). This study proposes an interval quasi-Monte Carlo simulation methodology to efficiently compute the bounds of structure failure probabilities. The methodology is based on deterministic low-discrepancy sequences, which are distributed more regularly than the (pseudo) random points in direct Monte Carlo simulation. The efficiency and accuracy of the present method is illustrated using two examples. The reliability implications of different approaches for construction of probability boxes are also investigated through the example.

Externe Organisation(en)

The University of Liverpool
Harbin Institute of Technology
Universität Sydney

Typ

Artikel

Journal

Mechanical Systems and Signal Processing

Band

37

Seiten

137-151

Anzahl der Seiten

15

ISSN

0888-3270

Publikationsdatum

05.2013

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Steuerungs- und Systemtechnik, Signalverarbeitung, Tief- und Ingenieurbau, Luft- und Raumfahrttechnik, Maschinenbau, Angewandte Informatik

Elektronische Version(en)

https://doi.org/10.1016/j.ymssp.2012.03.001 (Zugang: Geschlossen)