Latin hypercube sampling and updated Latin hypercube sampling method for reliability sensitivity and its variance analysis

Yue Wan, Zhenzhou Lu, Xiukai Yuan

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Latin hypercube sampling (LHS) and updated Latin hypercube sampling (ULHS) by statistical correlation reducing equation are employed to analyze structural reliability sensitivity and its variance. Numerical and engineering examples with single failure mode and with multiple failure modes are used to demonstrate the advantage of the LHS and ULHS based reliability sensitivity methods. The results of the illustrations show that the reliability sensitivity estimates based on the LHS and the ULHS are more robust than that on the Monte Carlo simulation in case of small sampling size. The unbiased estimate of the reliability sensitivity can be obtained by use of LHS. The variance of the sensitivity estimation based on ULHS can be reduced more than that based on LHS in small sampling size. The LHS and ULHS based structural reliability sensitivity method are independent of the distribution form and correlative characteristics of the basic random variable, thus they are effective and practicable for reliability sensitivity in small sampling size.

Original languageEnglish
Pages (from-to)927-934
Number of pages8
JournalJixie Qiangdu/Journal of Mechanical Strength
Volume30
Issue number6
StatePublished - Dec 2008

Keywords

  • Latin hypercube sampling
  • Monte Carlo
  • Statistical correlation reducing equation
  • Updated Latin hypercube sampling
  • Variance

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