A time-variant extreme-value event evolution method for time-variant reliability analysis

被引:33
作者
Ping, M. H. [1 ]
Han, X. [1 ]
Jiang, C. [1 ]
Xiao, X. Y. [1 ]
机构
[1] Hunan Univ, Coll Mech & Vehicle Engn, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China
基金
美国国家科学基金会;
关键词
Time-variant reliability; Extreme-value event evolution; Univariate dimension reduction method; Time-dependent polynomial chaos expansion method; EQUIVALENT LINEARIZATION; STRUCTURAL RELIABILITY; APPROXIMATIONS; SIMULATION;
D O I
10.1016/j.ymssp.2019.05.009
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
In this paper, we propose a time-variant extreme-value event evolution method (TEEM). The time-evolution process of extreme-value event is firstly proposed in this paper. And by solving it, we can obtain the time-variant reliability of arbitrary time interval and arbitrary failure threshold. In this method, the random process in limit-state function is firstly expanded by an improved orthogonal series expansion method (iOSE). Second, we introduce the idea of extreme-value event to describe the time-variant reliability problem. And by discretizing the time domain, we can obtain a series of extreme-value events. The moments of extreme-value event in every discrete time interval will be solved by the integration of Broyden-Fletcher-Goldfarb-Shanno (BFGS) method and univariate dimension reduction method (UDRM). Third, a time-dependent polynomial chaos expansion method (t-PCE) is proposed to simulate the extreme-value event's time-evolution process, and it will be simulated as a function in terms of a standard normal variable and time. Finally, Monte Carlo simulation (MCS) is adopted to sample the standard normal variable to obtain the time-variant reliability of arbitrary failure threshold and time interval. Three numerical examples are investigated to demonstrate the effectiveness of the proposed methods. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码:333 / 348
页数:16
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