New efficient and robust method for structural reliability analysis and its application in reliability-based design optimization

2020 ◽  
Vol 366 ◽  
pp. 113018 ◽  
Author(s):  
Meide Yang ◽  
Dequan Zhang ◽  
Xu Han
Keyword(s):  
Design Optimization ◽  
Reliability Analysis ◽  
Structural Reliability ◽  
Robust Method ◽  
Reliability Based Design Optimization ◽  
Structural Reliability Analysis ◽  
Reliability Based Design

scholarly journals Structural reliability under uncertainty in moments: distributionally-robust reliability-based design optimization

2021 ◽  
Author(s):  
Yoshihiro Kanno
Keyword(s):  
Design Optimization ◽  
Optimization Problem ◽  
Structural Reliability ◽  
Reliability Based Design Optimization ◽  
Input Distribution ◽  
Reliability Based Design ◽  
Optimal Value ◽  
Reliability Constraint ◽  
Distributionally Robust ◽  
Robust Reliability

AbstractThis study considers structural optimization under a reliability constraint, in which the input distribution is only partially known. Specifically, when it is only known that the expected value vector and the variance-covariance matrix of the input distribution belong to a given convex set, it is required that the failure probability of a structure should be no greater than a specified target value for any realization of the input distribution. We demonstrate that this distributionally-robust reliability constraint can be reduced equivalently to deterministic constraints. By using this reduction, we can handle a reliability-based design optimization problem under the distributionally-robust reliability constraint within the framework of deterministic optimization; in particular, nonlinear semidefinite programming. Two numerical examples are solved to demonstrate the relation between the optimal value and either the target reliability or the uncertainty magnitude.

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.

scholarly journals A decoupling algorithm with first-order asymptotic integration for reliability-based design optimization

2018 ◽  
Vol 10 (9) ◽  
pp. 168781401879333 ◽  
Author(s):  
Zhiliang Huang ◽  
Tongguang Yang ◽  
Fangyi Li
Keyword(s):  
Design Optimization ◽  
Reliability Analysis ◽  
Optimization Problems ◽  
Asymptotic Integration ◽  
Probabilistic Constraints ◽  
Reliability Based Design Optimization ◽  
First Order Reliability Method ◽  
First Order ◽  
Reliability Based Design ◽  
Reliability Method

Conventional decoupling approaches usually employ first-order reliability method to deal with probabilistic constraints in a reliability-based design optimization problem. In first-order reliability method, constraint functions are transformed into a standard normal space. Extra non-linearity introduced by the non-normal-to-normal transformation may increase the error in reliability analysis and then result in the reliability-based design optimization analysis with insufficient accuracy. In this article, a decoupling approach is proposed to provide an alternative tool for the reliability-based design optimization problems. To improve accuracy, the reliability analysis is performed by first-order asymptotic integration method without any extra non-linearity transformation. To achieve high efficiency, an approximate technique of reliability analysis is given to avoid calculating time-consuming performance function. Two numerical examples and an application of practical laptop structural design are presented to validate the effectiveness of the proposed approach.

RELIABILITY DESIGN EVALUATION AND OPTIMIZATION OF A NITROGEN GAS BOTTLE USING RESPONSE SURFACE METHOD

2010 ◽  
Vol 17 (02) ◽  
pp. 119-132 ◽  
Author(s):  
P. BHATTACHARJEE ◽  
K. RAMESH KUMAR ◽  
T. A. JANARDHAN REDDY
Keyword(s):  
Design Optimization ◽  
Response Surface ◽  
Response Surface Method ◽  
Structural Reliability ◽  
Operating Conditions ◽  
Optimization Under Uncertainty ◽  
Reliability Based Design Optimization ◽  
Nitrogen Gas ◽  
Reliability Based Design ◽  
Surface Method

Optimization of any aerospace product results in increasing payload capacity of space vehicles. Essentially weight, volume and cost are the main constraints. Design optimization studies for aerospace system are increasingly gaining importance. The problem of optimum design under uncertainty has been formulated as reliability-based design optimization. The reliability based optimization, which includes robustness requirements leads to multi-objective optimization under uncertainty. In this paper Reliability, based design optimization study is carried out under linear constraint optimization to minimize the weight of a nitrogen gas bottle with specified target reliability. Response surface method considering full factorial experiment is used to establish multiple regression equation for induced hoop stress and maximum strain. Necessary data pertaining to design, manufacturing and operating conditions are collected systematically for variability study. Structural reliability is evaluated using Advanced First-Order Second-Moment Method (AFOSM). Finally, optimization formulation established and it has been discussed in this paper.

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