First order control variates algorithm for reliability analysis of engineering structures

被引:36
作者
Ghalehnovi, Mansour [1 ]
Rashki, Mohsen [2 ]
Ameryan, Ala [1 ]
机构
[1] Ferdowsi Univ Mashhad, Dept Civil Engn, Mashhad, Razavi Khorasan, Iran
[2] Univ Sistan & Baluchestan, Dept Architectural Engn, Zahedan, Iran
关键词
First order reliability; Control variates; Importance sampling; Most probable point; SAFETY INDEX CALCULATION; RESPONSE-SURFACE METHOD; MONTE-CARLO; SIMULATION METHOD; FAILURE; APPROXIMATE; PROBABILITY; MODEL;
D O I
10.1016/j.apm.2019.07.049
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This study introduces an efficient method for safety evaluation of the structures with small failure probability. The proposed approach reformulates basic failure probability formula based on control variates method and suggests to firstly substitute the nonlinear limit state function with a linear limit state function for taking the advantages of linear problems during reliability process. Reliability analysis of linear problems would be fully accurate and dimension insensitive. Subsequently, the control variates method imposes the effect of limit state function nonlinearity on the obtained first-order failure probability by using a very small sampling size simulation. The result is a new reliability formulation that is highly suitable for solving nonlinear and high dimension problems. The capabilities of the method examined by solving several benchmarks numerical/engineering problems involving non-normal random variables, complex/noisy limit state functions, and nonlinear high dimension problems. Compared with mainstream reliability methods, for all solved problems, it is demonstrated that the proposed approach presents accuracy close to Monte Carlo simulation while the required number of performance function valuation is close to first-order reliability method. (C) 2019 Elsevier Inc. All rights reserved.
引用
收藏
页码:829 / 847
页数:19
相关论文
共 57 条
[51]   An efficient reliability algorithm for locating design point using the combination of importance sampling concepts and response surface method [J].
Shayanfar, Mohsen Ali ;
Barkhordari, Mohammad Ali ;
Roudak, Mohammad Amin .
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2017, 47 :223-237
[52]   Moment-based evaluation of structural reliability [J].
Wang, Cao ;
Zhang, Hao ;
Li, Quanwang .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2019, 181 :38-45
[53]   Safety index calculation using intervening variables for structural reliability analysis [J].
Wang, LP ;
Grandhi, RV .
COMPUTERS & STRUCTURES, 1996, 59 (06) :1139-1148
[54]  
WANG LP, 1994, COMPUT STRUCT, V52, P103
[55]   Structural reliability analysis by univariate decomposition and numerical integration [J].
Wei, D. ;
Rahman, S. .
PROBABILISTIC ENGINEERING MECHANICS, 2007, 22 (01) :27-38
[56]   Structural Reliability Analysis Using Combined Space Partition Technique and Unscented Transformation [J].
Xiao, Sinan ;
Lu, Zhenzhou .
JOURNAL OF STRUCTURAL ENGINEERING, 2016, 142 (11)
[57]   A new unbiased metamodel method for efficient reliability analysis [J].
Xue, Guofeng ;
Dai, Hongzhe ;
Zhang, Hao ;
Wang, Wei .
STRUCTURAL SAFETY, 2017, 67 :1-10