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

Abstract 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.

[1]  P. Spanos,et al.  Galerkin Scheme-Based Determination of Survival Probability of Oscillators With Fractional Derivative Elements , 2016 .

[2]  C. G. Broyden The Convergence of a Class of Double-rank Minimization Algorithms 1. General Considerations , 1970 .

[3]  D. Shanno Conditioning of Quasi-Newton Methods for Function Minimization , 1970 .

[4]  Arvid Naess,et al.  Reliability of Strongly Nonlinear Single Degree of Freedom Dynamic Systems by the Path Integration Method , 2008 .

[5]  Bruno Sudret,et al.  Analytical derivation of the outcrossing rate in time-variant reliability problems , 2008 .

[6]  Jie Liu,et al.  Time-Variant Reliability Analysis through Response Surface Method , 2017 .

[7]  Xiaoping Du,et al.  Simulation-based time-dependent reliability analysis for composite hydrokinetic turbine blades , 2013 .

[8]  Aldo Tagliani,et al.  On the existence of maximum entropy distributions with four and more assigned moments , 1990 .

[9]  Robert F. Pawula,et al.  Generalizations and extensions of the Fokker- Planck-Kolmogorov equations , 1967, IEEE Trans. Inf. Theory.

[10]  Isaac Elishakoff,et al.  Refined second-order reliability analysis☆ , 1994 .

[11]  Jianbing Chen,et al.  The extreme value distribution and dynamic reliability analysis of nonlinear structures with uncertain parameters , 2007 .

[12]  Zhen Hu,et al.  A Sampling Approach to Extreme Value Distribution for Time-Dependent Reliability Analysis , 2013 .

[13]  C. Bucher,et al.  A fast and efficient response surface approach for structural reliability problems , 1990 .

[14]  Dongbin Xiu,et al.  The Wiener-Askey Polynomial Chaos for Stochastic Differential Equations , 2002, SIAM J. Sci. Comput..

[15]  R. Rackwitz,et al.  Non-Normal Dependent Vectors in Structural Safety , 1981 .

[16]  R. Rackwitz,et al.  Structural reliability under combined random load sequences , 1978 .

[17]  Franck Schoefs,et al.  Time-variant reliability analysis using polynomial chaos expansion , 2015 .

[18]  S. Rahman,et al.  A univariate dimension-reduction method for multi-dimensional integration in stochastic mechanics , 2004 .

[19]  Bruno Sudret,et al.  The PHI2 method: a way to compute time-variant reliability , 2004, Reliab. Eng. Syst. Saf..

[20]  Zhen Hu,et al.  Mixed Efficient Global Optimization for Time-Dependent Reliability Analysis , 2015 .

[21]  Jianbing Chen,et al.  The probability density evolution method for dynamic response analysis of non‐linear stochastic structures , 2006 .

[22]  A. M. Hasofer,et al.  Exact and Invariant Second-Moment Code Format , 1974 .

[23]  Dequan Zhang,et al.  A time-variant reliability analysis method based on stochastic process discretization , 2014 .

[24]  Yao Wang,et al.  Time-Dependent Reliability-Based Design Optimization Utilizing Nonintrusive Polynomial Chaos , 2013, J. Appl. Math..

[25]  J. Beck,et al.  A new adaptive importance sampling scheme for reliability calculations , 1999 .

[26]  Pol D. Spanos,et al.  Survival Probability Determination of Nonlinear Oscillators Subject to Evolutionary Stochastic Excitation , 2014 .

[27]  Pingfeng Wang,et al.  A new approach for reliability analysis with time-variant performance characteristics , 2013, Reliab. Eng. Syst. Saf..

[28]  K. Breitung Asymptotic approximations for multinormal integrals , 1984 .

[29]  Donald R. Jones,et al.  Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..

[30]  G. Schuëller,et al.  Equivalent linearization and Monte Carlo simulation in stochastic dynamics , 2003 .

[31]  J. J. Coleman Reliability of Aircraft Structures in Resisting Chance Failure , 1959 .

[32]  Bruce R. Ellingwood,et al.  Orthogonal Series Expansions of Random Fields in Reliability Analysis , 1994 .

[33]  Jianbing Chen,et al.  The equivalent extreme-value event and evaluation of the structural system reliability , 2007 .

[34]  Karl Breitung,et al.  Probability Approximations by Log Likelihood Maximization , 1991 .

[35]  Xiaoping Du,et al.  Time-dependent reliability analysis with joint upcrossing rates , 2013 .

[36]  S. Rice Mathematical analysis of random noise , 1944 .

[37]  R. Fletcher,et al.  A New Approach to Variable Metric Algorithms , 1970, Comput. J..

[38]  Pingfeng Wang,et al.  A Nested Extreme Response Surface Approach for Time-Dependent Reliability-Based Design Optimization , 2012 .

[39]  D. Goldfarb A family of variable-metric methods derived by variational means , 1970 .

[40]  Xiaoping Du,et al.  Uncertainty Analysis by Dimension Reduction Integration and Saddlepoint Approximations , 2005, DAC 2005.

[41]  Sharif Rahman,et al.  A generalized dimension‐reduction method for multi‐dimensional integration in stochastic mechanics (Int. J. Numer. Meth. Engng 2004; 61:1992–2019) , 2006 .

[42]  T. Caughey Equivalent Linearization Techniques , 1962 .

[43]  R. Rackwitz,et al.  Approximations of first-passage times for differentiable processes based on higher-order threshold crossings , 1995 .