Coupled fuzzy-interval model and method for structural response analysis with non-probabilistic hybrid uncertainties

被引:18
|
作者
Wang, Chong [1 ,2 ]
Matthies, Hermann G. [2 ]
机构
[1] Beihang Univ, Inst Solid Mech, Beijing 100191, Peoples R China
[2] Tech Univ Carolo Wilhelmina Braunschweig, Inst Sci Comp, D-38106 Braunschweig, Germany
关键词
Non-probabilistic hybrid uncertainties; Interval and fuzzy analysis; Coupled fuzzy-interval model; Conservative and radical extreme-value prediction; Adaptive response surface method; Potential global optimum points; RELIABILITY-ANALYSIS; OPTIMIZATION; SYSTEM;
D O I
10.1016/j.fss.2020.06.002
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In many engineering practices with uncertainty, the non-probabilistic methods play an increasing important role. To overcome the limitation of traditional single-uncertainty modeling methods in handling coupled uncertain problems, this paper develops a more general hybrid uncertainty analysis framework. The non-probabilistic hybrid uncertainties are expressed as coupled fuzzy-interval variables, where the bounds of interval are interpreted as fuzzy sets instead of deterministic values. By means of the cut-set strategy and decomposition theorem in fuzzy set theory, the hybrid uncertain problem is transformed into a series of dual-interval problems. The conservative and radical extreme-value predictions in different variable subspaces are adopted to characterize the coupled uncertainty in output response. To further improve the computational efficiency of extreme-value prediction, an adaptive response surface model using radial basis function is proposed, where the potential global optimum points are introduced as the new sample points in the sequential sampling process. Finally, the effectiveness of the proposed method on dealing with non-probabilistic hybrid uncertainties is validated by two examples. (c) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码:171 / 189
页数:19
相关论文
共 50 条
  • [11] Non-probabilistic fuzzy reliability analysis of slope stability based on interval interconnection method
    Cao, Wengui
    Zhang, Yongjie
    Tumu Gongcheng Xuebao/China Civil Engineering Journal, 2007, 40 (11): : 64 - 69
  • [12] Non-probabilistic interval analysis method for dynamic response analysis of nonlinear systems with uncertainty
    Qiu, Zhiping
    Ma, Lihong
    Wang, Xiaojun
    JOURNAL OF SOUND AND VIBRATION, 2009, 319 (1-2) : 531 - 540
  • [13] A non-probabilistic model for structural reliability analysis
    Qiao, Xinzhou
    Qiu, Yuanying
    FRONTIERS OF MANUFACTURING AND DESIGN SCIENCE IV, PTS 1-5, 2014, 496-500 : 2737 - +
  • [14] Non-probabilistic wavelet method to consider uncertainties in structural damage detection
    Abdulkareem, Muyideen
    Bakhary, Norhisham
    Vafaei, Mohammadreza
    Noor, Norhazilan Md
    Padil, Khairul H.
    JOURNAL OF SOUND AND VIBRATION, 2018, 433 : 77 - 98
  • [15] A non-probabilistic time-variant reliable control method for structural vibration suppression problems with interval uncertainties
    Wang, Lei
    Wang, Xiaojun
    Li, Yunlong
    Hu, Juxi
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2019, 115 : 301 - 322
  • [16] Theoretical analysis of non-probabilistic reliability based on interval model
    Chen, Xu-Yong
    Fan, Jian-Ping
    Bian, Xiao-Ya
    ACTA MECHANICA SOLIDA SINICA, 2017, 30 (06) : 638 - 646
  • [17] Theoretical analysis of non-probabilistic reliability based on interval model
    Xu-Yong Chen
    Jian-Ping Fanb
    Xiao-Ya Bian
    Acta Mechanica Solida Sinica, 2017, 30 : 638 - 646
  • [18] A hybrid computational model for non-probabilistic uncertainty analysis
    Silva, R. S.
    Almeida, R. C.
    PROCEEDINGS OF LSAME.08: LEUVEN SYMPOSIUM ON APPLIED MECHANICS IN ENGINEERING, PTS 1 AND 2, 2008, : 859 - 868
  • [19] Theoretical analysis of non-probabilistic reliability based on interval model
    Xu-Yong Chen
    Jian-Ping Fan
    Xiao-Ya Bian
    ActaMechanicaSolidaSinica, 2017, 30 (06) : 638 - 646
  • [20] A new non-probabilistic time-dependent reliability model for mechanisms with interval uncertainties
    Chang, Qi
    Zhou, Changcong
    Wei, Pengfei
    Zhang, Yishang
    Yue, Zhufeng
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2021, 215