Variance-based reliability sensitivity analysis and the FORM α-factors

被引:50
作者
Papaioannou, Iason [1 ]
Straub, Daniel [1 ]
机构
[1] Tech Univ Munich, Engn Risk Anal Grp, Arcisstr 21, D-80290 Munich, Germany
关键词
Reliability analysis; Sensitivity analysis; alpha-factors; FORM; INDEPENDENT IMPORTANCE MEASURE; STRUCTURAL RELIABILITY; OPTIMIZATION; ALGORITHMS;
D O I
10.1016/j.ress.2021.107496
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In reliability assessments, it is useful to compute importance measures that provide information on the influence of the input random variables on the probability of failure. Classical importance measures are the alpha-factors, which are obtained as a by-product of the first-order reliability method (FORM). These factors are the directional cosines of the most probable failure point in an underlying independent standard normal space. Alternatively, one might assess sensitivity by a variance decomposition of the indicator function, i.e., the function that indicates membership of the random variables to the failure domain. This paper discusses the relation of the latter variance-based sensitivity measures to the FORM alpha-factors and analytically shows that there exist one-to-one relationships between them for linear limit-state functions of normal random variables. We also demonstrate that these relationships enable a good approximation of variance-based sensitivities for general reliability problems. The derived relationships shed light on the behavior of first-order and total-effect indices of the failure event in engineering reliability problems.
引用
收藏
页数:8
相关论文
共 44 条
[31]   Assessment and design of an engineering structure with polymorphic uncertainty quantification [J].
Papaioannou I. ;
Daub M. ;
Drieschner M. ;
Duddeck F. ;
Ehre M. ;
Eichner L. ;
Eigel M. ;
Götz M. ;
Graf W. ;
Grasedyck L. ;
Gruhlke R. ;
Hömberg D. ;
Kaliske M. ;
Moser D. ;
Petryna Y. ;
Straub D. .
GAMM Mitteilungen, 2019, 42 (02)
[32]  
Papaioannou I, 2009, P 2 INT C COMP METH
[33]   Improved cross entropy-based importance sampling with a flexible mixture model [J].
Papaioannou, Iason ;
Geyer, Sebastian ;
Straub, Daniel .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2019, 191
[34]   Reliability sensitivity estimation with sequential importance sampling [J].
Papaioannou, Iason ;
Breitung, Karl ;
Straub, Daniel .
STRUCTURAL SAFETY, 2018, 75 :24-34
[35]   Sequential importance sampling for structural reliability analysis [J].
Papaioannou, Iason ;
Papadimitriou, Costas ;
Straub, Daniel .
STRUCTURAL SAFETY, 2016, 62 :66-75
[36]   Efficient Evaluation of Reliability-Oriented Sensitivity Indices [J].
Perrin, G. ;
Defaux, G. .
JOURNAL OF SCIENTIFIC COMPUTING, 2019, 79 (03) :1433-1455
[37]  
Prieur C., 2017, Handbook of Uncertainty Quantification. Ed. by, P1217
[38]  
Ranjan R, 2013, P 3 INT C COMP METH
[39]  
Sobol I.M., 1993, Math. Model. Comput. Exp., V1, P407, DOI DOI 10.18287/0134-2452-2015-39-4-459-461
[40]   Subset simulation for structural reliability sensitivity analysis [J].
Song, Shufang ;
Lu, Zhenzhou ;
Qiao, Hongwei .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2009, 94 (02) :658-665