液体火箭发动机自适应克里金可靠性分析

Adaptive Kriging-Based Reliability Analysis for Liquid Rocket Engine

针对液体火箭发动机运行过程中外界载荷及自身属性存在不确定性导致失效的问题,提出了一种基于泰森多边形区域划分结合自适应克里金代理模型的液体火箭发动机可靠性分析方法。该方法通过对全局进行泰森多边形区域划分,结合改进留一法选取最敏感区域,通过主动学习函数筛选样本点,进而迭代更新液体火箭发动机的克里金代理模型。该方法的优势在于,能够依据较少的样本点构建精确的液体火箭发动机模型,实现液体火箭发动机失效概率的准确预测。将本文所提方法应用于实际液体火箭发动机可靠性分析中,构建的代理模型测试计算误差与其他模型相比小于1%,效率提高了48%,从而高效地实现了液体火箭发动机的可靠性分析,降低了计算成本。

A reliability analysis method of liquid rocket engine using a new adaptive Kriging based on voronoi-region-partition important sampling is proposed to solve the problem that the external load and its own attributes are uncertain and can lead to failure during the operation of liquid rocket engine. The method is based on global voronoi-region-partition, which is combined with improved leave-one-out method to select the most sensitive regions through active learning function selection of sample points and then iterative updating liquid rocket engine kriging model. The method can use fewer sample data to establish the mathematical model for liquid rocket engine to realize the failure probability of accurate prediction. The simulation results show that the proposed method can effectively realize the reliability analysis of liquid rocket engine and reduce the calculation cost.