Iterative reliable design space approach for efficient reliability-based design optimization

2019 ◽  
Vol 36 (1) ◽  
pp. 151-169 ◽  
Author(s):  
Chen Jiang ◽  
Haobo Qiu ◽  
Xiaoke Li ◽  
Zhenzhong Chen ◽  
Liang Gao ◽  
...  
Keyword(s):  
Design Optimization ◽  
Design Space ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design ◽  
Reliable Design ◽  
Space Approach

Reliable Space Pursuing for RBDO With Black-Box Performance Functions

2007 ◽  
Author(s):  
S. Shan ◽  
G. Gary Wang
Keyword(s):  
Design Space ◽  
Reliability Assessment ◽  
Black Box ◽  
Double Loop ◽  
High Current ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design ◽  
Reliable Design ◽  
Loop Procedure ◽  
Very High

Reliability-based design optimization (RBDO) is intrinsically a double-loop procedure since it involves an overall optimization and an iterative reliability assessment at each search point. Due to the double-loop procedure, the computational expense of RBDO is normally very high. Current RBDO research is focused on performance functions having explicit analytical expression and readily available gradients. This paper addresses a more challenging type of RBDO problem in which the performance functions are computation intensive. These computation intensive functions are often considered as a “black-box” and their gradients are not available or not reliable. Based on the reliable design space (RDS) concept proposed earlier by the authors, this paper proposes a Reliable Space Pursuing (RSP) approach, in which RDS is first identified and then gradually refined while optimization is performed. It theoretically avoids the nested optimization and probabilistic assessment loop. This approach can apply to RBDO problems with either analytical or blackbox performance functions. Three well known numerical problems from the literature are used to test and demonstrate the effectiveness of RSP.

Model Uncertainty Approximation Using a Copula-Based Approach for Reliability Based Design Optimization

2016 ◽  
Author(s):  
Hao Pan ◽  
Zhimin Xi ◽  
Ren-Jye Yang
Keyword(s):  
Design Optimization ◽  
Model Uncertainty ◽  
Design Space ◽  
Epistemic Uncertainty ◽  
Minimum Cost ◽  
Vehicle Design ◽  
Model Bias ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design ◽  
Model Inadequacy

Reliability-based design optimization (RBDO) has been widely used to design engineering products with minimum cost function while meeting defined reliability constraints. Although uncertainties, such as aleatory uncertainty and epistemic uncertainty, have been well considered in RBDO, they are mainly considered for model input parameters. Model uncertainty, i.e., the uncertainty of model bias which indicates the inherent model inadequacy for representing the real physical system, is typically overlooked in RBDO. This paper addresses model uncertainty characterization in a defined product design space and further integrates the model uncertainty into RBDO. In particular, a copula-based bias correction approach is proposed and results are demonstrated by two vehicle design case studies.

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