Solving Time-dependent reliability-based design optimization by adaptive differential evolution algorithm and time-dependent polynomial chaos expansions (ADE-T-PCE)

2020 ◽  
Vol 114 ◽  
pp. 113815
Author(s):  
Xuerong Ye ◽  
Hao Chen ◽  
Qiankun Kuang ◽  
Yue Wang ◽  
Hao Niu ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Design Optimization ◽  
Polynomial Chaos ◽  
Differential Evolution Algorithm ◽  
Time Dependent ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design ◽  
Adaptive Differential Evolution ◽  
Evolution Algorithm ◽  
Polynomial Chaos Expansions

scholarly journals Time-Dependent Reliability-Based Design Optimization Utilizing Nonintrusive Polynomial Chaos

2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
Yao Wang ◽  
Shengkui Zeng ◽  
Jianbin Guo
Keyword(s):  
Design Optimization ◽  
Structural Reliability ◽  
Polynomial Chaos ◽  
Time Dependent ◽  
Fe Model ◽  
Reliability Based Design Optimization ◽  
Wear Process ◽  
Reliability Based Design ◽  
Optimization Methodology ◽  
Wear Law

Time-dependent reliability-based design optimization (RBDO) has been acknowledged as an advance optimization methodology since it accounts for time-varying stochastic nature of systems. This paper proposes a time-dependent RBDO method considering both of the time-dependent kinematic reliability and the time-dependent structural reliability as constrains. Polynomial chaos combined with the moving least squares (PCMLS) is presented as a nonintrusive time-dependent surrogate model to conduct uncertainty quantification. Wear is considered to be a critical failure that deteriorates the kinematic reliability and the structural reliability through the changing kinematics. According to Archard’s wear law, a multidiscipline reliability model including the kinematics model and the structural finite element (FE) model is constructed to generate the stochastic processes of system responses. These disciplines are closely coupled and uncertainty impacts are cross-propagated to account for the correlationship between the wear process and loads. The new method is applied to an airborne retractable mechanism. The optimization goal is to minimize the mean and the variance of the total weight under both of the time-dependent and the time-independent reliability constraints.

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