Model uncertainty approximation using a copula-based approach for reliability based design optimization

被引:22
作者
Pan, Hao [1 ]
Xi, Zhimin [1 ]
Yang, Ren-Jye [2 ]
机构
[1] Univ Michigan Dearborn, Dept Ind & Mfg Syst Engn, Dearborn, MI 48168 USA
[2] Ford Res & Adv Engn, MD2115-RIC,2101 Village Rd, Dearborn, MI 48121 USA
基金
美国国家科学基金会;
关键词
Model uncertainty; Reliability-based design optimization; Copula modeling; Bias correction; Vehicle design; POLYNOMIAL CHAOS EXPANSION; DIMENSION-REDUCTION METHOD; MULTIDIMENSIONAL INTEGRATION; CALIBRATION; QUANTIFICATION; PERFORMANCE; VALIDATION; FRAMEWORK;
D O I
10.1007/s00158-016-1530-2
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Reliability-based design optimization (RBDO) has been widely used to design engineering products with minimum cost function while meeting 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 indicating the inherent model inadequacy for representing the real physical system, is typically overlooked in RBDO. This paper addresses model uncertainty approximation in a product design space and further integrates the model uncertainty into RBDO. In particular, a copula-based bias modeling approach is proposed and results are demonstrated by two vehicle design problems.
引用
收藏
页码:1543 / 1556
页数:14
相关论文
共 65 条
[1]   An inverse-measure-based unilevel architecture for reliability-based design optimization [J].
Agarwal, Harish ;
Mozumder, Chandan K. ;
Renaud, John E. ;
Watson, Layne T. .
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2007, 33 (03) :217-227
[2]   New decoupled framework for reliability-based design optimization [J].
Agarwal, Harish ;
Renaud, John E. .
AIAA JOURNAL, 2006, 44 (07) :1524-1531
[3]  
[Anonymous], SAMBA2406 NORW COMP
[4]  
[Anonymous], SOC ACT 2008 ENT RIS
[5]  
[Anonymous], J AM STAT ASS, DOI DOI 10.1198/016214507000000888
[6]  
[Anonymous], 1959, ANN LISUP
[7]   A new adaptive importance sampling scheme for reliability calculations [J].
Au, SK ;
Beck, JL .
STRUCTURAL SAFETY, 1999, 21 (02) :135-158
[8]   An illustration of the use of an approach for treating model uncertainties in risk assessment [J].
Bjerga, Torbjorn ;
Aven, Terje ;
Zio, Enrico .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2014, 125 :46-53
[9]   Thermal problem solution using a surrogate model clustering technique [J].
Brandyberry, Mark D. .
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2008, 197 (29-32) :2390-2407
[10]   ADAPTIVE SAMPLING - AN ITERATIVE FAST MONTE-CARLO PROCEDURE [J].
BUCHER, CG .
STRUCTURAL SAFETY, 1988, 5 (02) :119-126