A new uncertainty propagation method for problems with parameterized probability-boxes

被引:49
|
作者
Liu, H. B. [1 ]
Jiang, C. [1 ]
Jia, X. Y. [1 ]
Long, X. Y. [1 ]
Zhang, Z. [1 ]
Guan, F. J. [2 ]
机构
[1] Hunan Univ, Coll Mech & Vehicle Engn, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China
[2] Natl Univ Def Technol, Sci & Technol Integrated Logist Support Lab, Changsha 410082, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
Parameterized p-boxes; Uncertainty propagation; Dimension reduction method; Probability bounds; Johnson distribution; DIMENSION-REDUCTION METHOD; MULTIDIMENSIONAL INTEGRATION; IMPRECISE PROBABILITIES; POLYNOMIAL CHAOS; REPRESENTATION;
D O I
10.1016/j.ress.2017.12.004
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper proposes a new uncertainty propagation method for problems with parameterized probability-boxes (p-boxes), which could efficiently compute the probability bounds of system response function. In practical engineering, these probability bounds are often very important for reliability analysis or risk assessment of a structure or system. First, based on the univariate dimension reduction method (UDRM), an optimized UDRM (OUDRM) is presented to calculate the bounds on statistical moments of response function. Then, utilizing the bounds on moments, a family of Johnson distributions fitting to the distribution function of response can be acquired using the moment matching method. Finally, by using an optimization approach based on percentiles, the probability bounds of the response function can be successfully obtained. Four numerical examples are investigated to demonstrate the effectiveness of the proposed method. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:64 / 73
页数:10
相关论文
共 50 条
  • [31] A new generalized parameterized inexact Uzawa method for solving saddle point problems
    Dai, Lifang
    Liang, Maolin
    Fan, Hongtao
    APPLIED MATHEMATICS AND COMPUTATION, 2015, 265 : 414 - 430
  • [32] A new structural reliability analysis method under non-parameterized probability box variables
    Huichao Xie
    Jinwen Li
    Daihui Liao
    Structural and Multidisciplinary Optimization, 2022, 65
  • [34] An Intrusive Method for the Uncertainty Propagation
    Dossantos-Uzarralde, P.
    Nimal, V.
    Dejonghe, G.
    Sancandi, M.
    Andre, R.
    Hilaire, S.
    JOURNAL OF THE KOREAN PHYSICAL SOCIETY, 2011, 59 (02) : 1260 - 1263
  • [35] A novel uncertainty propagation and probability assessment method for the frequency response function involving correlated uncertainties
    Liao, Baopeng
    ARCHIVE OF APPLIED MECHANICS, 2024, 94 (06) : 1553 - 1573
  • [36] A new structural reliability analysis method under non-parameterized probability box variables
    Xie, Huichao
    Li, Jinwen
    Liao, Daihui
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2022, 65 (11)
  • [37] Uncertainty propagation of p-boxes using sparse polynomial chaos expansions
    Schobi, Roland
    Sudret, Bruno
    JOURNAL OF COMPUTATIONAL PHYSICS, 2017, 339 : 307 - 327
  • [38] A new software implementation of the Oslo method with rigorous statistical uncertainty propagation
    Midtbo, Jorgen E.
    Zeiser, Fabio
    Lima, Erlend
    Larsen, Ann-Cecilie
    Tveten, Gry M.
    Guttormsen, Magne
    Garrote, Frank Leonel Bello
    Kvellestad, Anders
    Renstrom, Therese
    COMPUTER PHYSICS COMMUNICATIONS, 2021, 262
  • [40] New method to compute truth-value propagation in uncertainty reasoning
    Fan, J.L.
    Ma, Y.L.
    Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, 2001, 21 (02):