论文标题
通过迭代密度估计对随机复合系统的设计优化
Design optimization of stochastic complex systems via iterative density estimation
论文作者
论文摘要
基于可靠性的设计优化（RBDO）提供了一个合理而合理的框架，用于查找最佳设计，同时将不确定性纳入AC计数。实施RBDO方法，尤其是基于随机模拟的方法的主要问题是评估可靠性约束的计算负担。在此贡献中，我们提出了一种有效的方法，该方法可促进故障概率函数（FPF）解除可靠性。基于增强概念，FPF的近似值等于故障设计样本的密度估计。与传统的密度估计方案不同，在整个设计空间中进行估计 - 在提出的方法中，我们根据故障设计样品的分布将设计空间迭代地将设计空间分配到几个子空间中。说明性示例的数值结果表明，促成方法可以大大改善计算性能。
Reliability-based design optimization (RBDO) provides a rational and sound framework for finding the optimal design while taking uncertainties into ac-count. The main issue in implementing RBDO methods, particularly stochastic simu-lation based ones, is the computational burden arising from the evaluation of reliability constraints. In this contribution, we propose an efficient method which ap-proximates the failure probability functions (FPF) to decouple reliability. Based on the augmentation concept, the approximation of FPF is equivalent to density estimation of failure design samples. Unlike traditional density estimation schemes, where the esti-mation is conducted in the entire design space, in the proposed method we iteratively partition the design space into several subspaces according to the distribution of fail-ure design samples. Numerical results of an illustrative example indicate that the pro-posed method can improve the computational performance considerably.
