基于发生函数法建立了含共因失效的多状态系统可靠性分析模型，通过改进的发生函数法求取多状态不可修串并联系统的可靠度函数。具体分两个步骤：第一步，先不考虑共因元件组的影响，用发生函数表示系统的性能分布；第二步，在“系统层”对共因元件组元件各状态信息进行分析，再用分析结果对系统发生函数进行修正，最终得到系统可靠度函数。

针对某航空发动机低压涡轮工作叶片建立了全尺寸有限元模型。根据台架试验及实际工作承载条件,综合考虑叶片工作时所承受的离心负荷与气流力，进行了弹塑性有限元分析；研究了箍带与叶身小孔的配合间隙对结构应力场分布的影响，发现叶片结构强度的薄弱之处为榫头第一喉部、叶身小孔及叶背一侧圆根处。以此为依据,对叶片进行了高温低循环疲劳寿命预测。计算结果表明：叶身小孔与箍带的最大配合间隙对结构静强度及寿命影响较大，寿命计算时应当考虑平均间隙量的影响；随着计算温度的提高，寿命计算结果大幅度下降。

文章分析了生产线制造过程的数字化制造环境，提出了基于扩展事件过程链的生产线制造过程建模仿真方法。在此基础上，采用面向对象软件方法，详细设计和实现了生产线制造过程建模仿真系统的各个组成模块。该软件系统应 用于实际生产线的规划设计，对生产线进行仿真分析和性能优化，与’149 其它子系统集成运行，提高了生产线制造过程的整体性能和经济效益。

In pressure vessels and piping the leak-before-break (LBB) assessment method is employed to avoid any catastrophic failure prior to a detectable leakage. One of the most important parameters, the leak rate, is investigated in the present paper by means of the Monte Carlo method. A brief reviewed is carried out with emphasis on aspects such as crack growth, crack size with detectable leakage, crack opening area and leak rate. Issues concerning the property and behavior of multiple cracks are also covered along with a review of the characteristics of leak rate through distributed multiple cracks using a statistical simulation method. The simulation results show that, the effect of multiple cracks is quite significant to the LBB concept. Both the relationship between leak rate and crack length (or time) and the statistical characteristics of the leak rate are considerably different for different initial crack conditions.

General failure event data from various sources are often used to estimate the failure probability for the system of interest, especially when s-dependence exists among component failures, where common cause failure plays an important role. Failure event data from different sources must be reasonably explained, and correctly applied, so that the information about load environment, and component/system property can be used correctly. In estimating the probability for s-dependent system failure, both the load distribution, and component strength distribution are much more important than component failure probability index.