Journal
RELIABILITY ENGINEERING & SYSTEM SAFETY
Volume 153, Issue -, Pages 170-179Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2016.05.002
Keywords
Reliability; Kriging; Surrogate model; Parallelizability
Funding
- National Natural Science Foundation of China [NSFC 51375388]
- Fundamental Research Funds for the Central Universities [14JCQ01038]
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The sequential Kriging reliability analysis (SKRA) method has been developed in recent years for non-linear implicit response functions which are expensive to evaluate. This type of method includes EGRA: the efficient reliability analysis method, and AK-MCS: the active learning reliability method combining Kriging model and Monte Carlo simulation. The purpose of this paper is to improve SKRA by adaptive sampling regions and parallelizability. The adaptive sampling regions strategy is proposed to avoid selecting samples in regions where the probability density is so low that the accuracy of these regions has negligible effects on the results. The size of the sampling regions is adapted according to the failure probability calculated by last iteration. Two parallel strategies are introduced and compared, aimed at selecting multiple sample points at a time. The improvement is verified through several troublesome examples. (C) 2016 Elsevier Ltd. All rights reserved.
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