时变可靠性分析的高效近似最大可能轨迹法

现有的时变可靠性分析方法在处理飞行器复杂时变可靠性分析问题时，存在求解效率过低的问题。在基于近似最大可能轨迹的时变可靠性分析方法的基础上，根据时间离散所得串联系统瞬时可靠度最小的组件决定整个系统可靠度的特点，在最大可能轨迹自适应建模过程中同时考虑轨迹模型的预测误差和预估值增加样本，提出时变可靠性分析的高效近似最大可能轨迹法；采用解析算例验证最大可能轨迹自适应采样方法的有效性，并将该可靠性分析方法应用于水动力涡轮叶片和某空天飞行器机翼的时变可靠性分析。结果表明：在精度相近的情况下，所提方法对极限状态函数调用次数不高于基于时间离散的可靠性分析方法的3%。

Efficient approximating the most-probable-point trajectory method for time-variant reliability analysis

Complex engineering systems such as aircraft are usually affected by uncertain factors, such as material performance degradation and time-varying loads during operation. When solving complex time-variant reliability analysis (TRA) problems, the developed methods usually cost a lot. In order to improve the efficiency of solving complex TRA problems, based on the approximating most-probable-points trajectory (AMPPT) method, the efficient approximating the most-probable-point trajectory (EAMPPT) method for TRA is proposed. According to the characteristics that the reliability of weakest part of the system determines the reliability of the system, EAMPPT takes full account of prediction values and their errors in the process of approximating the most-probable-point trajectory. A mathematical example demonstrates the effectiveness of the adaptive sampling method. EAMPPT is applied to solve TRA problems involving hydrokinetic turbine blades and the wing of the reusable aerospace during reenter. The results show that the calculation accuracy of the proposed EAMPPT and time-discretization based TRA (TDTRA) method is similar, but the number of performance function evaluations of EAMPPT is less than 3% of TDTRA.