L-Moments-Based FORM Method for Structural Reliability Analysis Considering Correlated Input Random Variables

被引:1
作者
Li, Zhi-Peng [1 ]
Hu, Dong-Zhu [1 ]
Zhang, Long-Wen [2 ]
Zhang, Zhen [3 ]
Shi, Yue [1 ]
机构
[1] Cent South Univ, Sch Civil Engn, 22 Shaoshannan Rd, Changsha 410075, Algeria
[2] Hunan Agr Univ, Coll Water Resources & Civil Engn, 1 Nongda Rd, Changsha 410128, Peoples R China
[3] Univ Wisconsin, Dept Civil & Environm Engn, Madison, WI 53706 USA
关键词
normal transformation; L-moments; correlated variables; statistical moments; structural reliability;
D O I
10.3390/buildings13051261
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Leveraging the properties of the first three linear moments (L-moments), this study proposes an effective normal transformation for structural reliability analysis considering correlated input random variables, in which the admissible range of the initial correlation matrix when employing this transformation is also presented. Subsequently, a practical procedure for structural reliability analysis, grounded in the proposed transformation and first-order reliability method (FROM), is proposed, accommodating instances wherein the joint probability density functions (PDFs) or marginal PDFs of the relevant random variables remain unknown. In comparison to the technique premised on the first three central moments (C-moments), the proposed method, based on the first three L-moments, exhibits a more extensive applicability. Various practical scenarios showcase the method's effectiveness and precision in calculating the structural reliability index, considering diverse distributions, numerous variables, and complex structures.
引用
收藏
页数:21
相关论文
共 27 条
  • [1] Bayesian post-processing of Monte Carlo simulation in reliability analysis
    Betz, Wolfgang
    Papaioannou, Iason
    Straub, Daniel
    [J]. RELIABILITY ENGINEERING & SYSTEM SAFETY, 2022, 227
  • [2] Correlated probabilistic load flow using a point estimate method with Nataf transformation
    Chen, Can
    Wu, Wenchuan
    Zhang, Boming
    Sun, Hongbin
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2015, 65 : 325 - 333
  • [3] Application of first-order reliability method with orthogonal plane sampling for high-dimensional series system reliability analysis
    Chen, Weiming
    Gong, Changqing
    Wang, Ziqi
    Frangopol, Dan M.
    [J]. ENGINEERING STRUCTURES, 2023, 282
  • [4] Investigation of polynomial normal transform
    Chen, XY
    Tung, YK
    [J]. STRUCTURAL SAFETY, 2003, 25 (04) : 423 - 445
  • [5] Estimation of Failure Probability Function under Imprecise Probabilities by Active Learning-Augmented Probabilistic Integration
    Dang, Chao
    Wei, Pengfei
    Song, Jingwen
    Beer, Michael
    [J]. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 2021, 7 (04)
  • [6] A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models
    Echard, B.
    Gayton, N.
    Lemaire, M.
    Relun, N.
    [J]. RELIABILITY ENGINEERING & SYSTEM SAFETY, 2013, 111 : 232 - 240
  • [7] Hybrid C- and L-Moment-Based Hermite Transformation Models for Non-Gaussian Processes
    Gao, S.
    Zheng, X. Y.
    Huang, Y.
    [J]. JOURNAL OF ENGINEERING MECHANICS, 2018, 144 (02)
  • [8] Second-order reliability methods: a review and comparative study
    Hu, Zhangli
    Mansour, Rami
    Olsson, Marten
    Du, Xiaoping
    [J]. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2021, 64 (06) : 3233 - 3263
  • [9] A new direct second-order reliability analysis method
    Huang, Xianzhen
    Li, Yuxiong
    Zhang, Yimin
    Zhang, Xufang
    [J]. APPLIED MATHEMATICAL MODELLING, 2018, 55 : 68 - 80
  • [10] Vulnerability analysis of steel roofing cladding: Influence of wind directionality
    Ji, Xiaowen
    Huang, Guoqing
    Zhang, Xinxin
    Kopp, Gregory A.
    [J]. ENGINEERING STRUCTURES, 2018, 156 : 587 - 597