A new unbiased metamodel method for efficient reliability analysis

被引：33

作者：

Xue, Guofeng ^{[1
,2
]}

Dai, Hongzhe ^{[1
,2
]}

Zhang, Hao ^{[3
]}

Wang, Wei ^{[1
,2
]}

机构：

[1] Harbin Inst Technol, Sch Civil Engn, Harbin 150090, Peoples R China

[2] Harbin Inst Technol, Minist Educ, Key Lab Struct Dynam Behav & Control, Harbin 150090, Peoples R China

[3] Univ Sydney, Sch Civil Engn, Sydney, NSW 2006, Australia

来源：

STRUCTURAL SAFETY | 2017年 / 67卷

基金：

澳大利亚研究理事会; 中国国家自然科学基金;

关键词：

Reliability; Metamodelling; Unbiased estimation; Markov chain simulation; Adaptive refinement; SMALL FAILURE PROBABILITIES; SENSITIVITY-ANALYSIS; SUBSET SIMULATION; KRIGING METHOD;

D O I：

10.1016/j.strusafe.2017.03.005

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Metamodel method is widely used in structural reliability analysis. A main limitation of this method is that it is difficult or even impossible to quantify the model uncertainty caused by the metamodel approximation. This paper develops an improved metamodel method which is unbiased and highly efficient. The new method formulates a probability of failure as a product of a metamodel-based probability of failure and a correction term, which accounts for the approximation error due to metamodel approximation. The correction term is constructed and estimated using the Markov chain simulation. An iterative scheme is further developed to adaptively improve the accuracy of the metamodel and the associated correction term. The accuracy and efficiency of the new metamodel method is illustrated and compared with the classical Kriging metamodel and high dimensional model representation methods using a number of numerical and structural examples. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：1 / 10

页数：10

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