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A probability feasible region enhanced important boundary sampling method for reliability-based design optimization
Structural and Multidisciplinary Optimization ( IF 3.9 ) Pub Date : 2020-09-05 , DOI: 10.1007/s00158-020-02702-4
Zihao Wu , Zhenzhong Chen , Ge Chen , Xiaoke Li , Chen Jiang , Xuehui Gan , Liang Gao , Shengze Wang

Reliability-based design optimization (RBDO) is powerful for probabilistic constraint problems. Metamodeling is usually used in RBDO to reduce the computational cost. Kriging model-based RBDO is very suitable to solve engineering problems with implicit constraint functions. However, the efficiency and accuracy of the kriging model constrain its use in RBDO. In this research, the importance boundary sampling (IBS) method is enhanced by the probability feasible region (PFR) method to fit kriging model with high accuracy. The proposed probability feasible region enhanced importance boundary sampling (PFRE-IBS) method selects sample points for inactive constraint functions only in its important region, thus reducing the number of sample points to improve the efficiency of sampling method. In order to verify the efficiency and accuracy of the proposed PFRE-IBS method, three RBDO problems are used in this paper. The comparison results with other sampling methods show that the proposed PFRE-IBS method is very efficient and accurate.



中文翻译:

基于可靠度的设计优化的概率可行区域增强重要边界采样方法

基于可靠性的设计优化(RBDO)对于概率约束问题非常强大。RBDO中通常使用元模型来减少计算成本。基于克里格模型的RBDO非常适合解决具有隐式约束函数的工程问题。但是,克里金模型的效率和准确性限制了它在RBDO中的使用。在这项研究中,重要边界采样(IBS)方法通过概率可行区域(PFR)方法得到了增强,以高精度拟合克里金模型。提出的概率可行区域增强重要性边界采样方法(PFRE-IBS)仅在重要区域内为非活动约束函数选择采样点,从而减少了采样点的数量,提高了采样方法的效率。为了验证所提出的PFRE-IBS方法的效率和准确性,本文使用了三个RBDO问题。与其他采样方法的比较结果表明,所提出的PFRE-IBS方法非常有效且准确。

更新日期:2020-09-07
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