A Novel Time-Variant Reliability Analysis Method Based on Failure Processes Decomposition for Dynamic Uncertain Structures

Abstract

Due to the uncertainties and the dynamic parameters from design, manufacturing, and working conditions, many engineering structures usually show uncertain and dynamic properties. This paper proposes a novel time-variant reliability analysis method using failure processes decomposition to transform the time-variant reliability problems to the time-invariant problems for dynamic structures under uncertainties. The transformation is achieved via a two-stage failure processes decomposition. First, the limit state function with high dimensional input variables and high order temporal parameters is transformed to a quadratic function of time based on the optimized time point in the first-stage failure processes decomposition. Second, based on the characteristics of the quadratic function and reliability criterion, the time-variant reliability problem is then transformed to a time-invariant system reliability problem in the second-stage failure processes decomposition. Then, the kernel density estimation (KDE) method is finally employed for the system reliability evaluation. Several examples are used to verify the effectiveness of the proposed method to demonstrate its efficiency and accuracy.

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Structural reliability analysis and uncertainties‐based collaborative design and optimization of turbine blades using surrogate model

“…Although many researches have been published in this field, challenges still exist for simulating the fluidstructure coupled effect of blades accurately in practical engineering, especially in the situation that there are high design dimensions and non-linearity MDO problems. [30][31][32][33][34][35][36] To solve the above problem, a fluid-structure multidisciplinary analysis approach is proposed here. The total pressure ratio and the adiabatic efficiency of blades are analyzed here by the given method.…”

Time-variant reliability analysis of a continuous system with strength deterioration based on subset simulation

“…Recently, SS has been widely used to evaluate dynamic structural reliability [19][20][21][22]. Li et al [19] developed a generalized SS approach to estimate the failure probabilities of multiple stochastic responses.…”

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