Threshold shift method for reliability-based design optimization

被引:21
|
作者
Goswami, Somdatta [1 ]
Chakraborty, Souvik [2 ,3 ]
Chowdhury, Rajib [4 ]
Rabczuk, Timon [5 ]
机构
[1] Bauhaus Univ Weimar, Inst Struct Mech, D-99423 Weimar, Germany
[2] Univ Notre Dame, Ctr Informat & Computat Sci, Notre Dame, IN 46556 USA
[3] Univ Notre Dame, Dept Aerosp & Mech Engn, Notre Dame, IN 46556 USA
[4] Indian Inst Technol Roorkee, Dept Civil Engn, Roorkee 247667, Uttar Pradesh, India
[5] King Saud Univ, Dept Comp Engn, Coll Comp & Informat Sci, Riyadh, Saudi Arabia
关键词
RBDO; Threshold shift method; PC-Kriging; Uncertainty; PERFORMANCE-MEASURE APPROACH; SINGLE-LOOP METHOD; POLYNOMIAL-CHAOS; STRUCTURAL OPTIMIZATION; UNCERTAINTY ANALYSIS; EFFICIENT; CRASHWORTHINESS; SENSITIVITY; ALGORITHM; RBDO;
D O I
10.1007/s00158-019-02310-x
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We present a novel approach, referred to as the "threshold shift method" (TSM), for reliability-based design optimization (RBDO). The proposed approach is similar in spirit with the sequential optimization and reliability analysis (SORA) method where the RBDO problem is decoupled into an optimization and a reliability analysis problem. However, unlike SORA that utilizes shift vector to shift the design variables within a constraint (independently), in TSM, we propose to shift the threshold of the constraints. We argue that modifying a constraint, either by shifting the design variables (SORA) or by shifting the threshold of the constraints (TSM), influences the other constraints of the system. Therefore, we propose to determine the thresholds for all the constraints by solving a single optimization problem. Additionally, the proposed TSM is equipped with an active-constraint determination scheme. To make the method scalable, a practical algorithm for TSM that utilizes two surrogate models is proposed. Unlike the conventional RBDO methods, the proposed approach has the ability to handle highly non-linear probabilistic constraints. The performance of the proposed approach is examined on six benchmark problems selected from the literature. The proposed approach yields excellent results outperforming other popular methods in literature. As for the computational efficiency, the proposed approach is found to be highly efficient, indicating it's future application to other real-life problems.
引用
收藏
页码:2053 / 2072
页数:20
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