混合不确定条件下的飞行器级间分离可靠性分析

为量化飞行器级间分离过程随机不确定性和认知不确定性的综合影响,结合概率和区间理论混合模型特点,提出了一种基于随机和区间理论混合模型的飞行器级间分离可靠性分析方法。面向高超声速飞行器分离任务需求,建立分离动力学仿真模型,针对级间分离结构的几何特点,设计了一种快速碰撞检测方法,进而构建了分离任务的可靠性分析混合模型。通 过将该模型转化为随机可靠性分析的无约束优化问题,考虑分离过程中复杂外力及力矩导致功能函数高度非线性的特点,利用高效全局优化和主动学习Kriging方法实现无约束优化问题高效求解。结合实例表明,该方法能够准确描述混合不确定性因素对飞行器分离过程的影响,给出了飞行器分离任务可靠性区间,可为飞行器分离方案的精细化设计提供决策支持。     

节点非独立失效下的局域网可靠性建模与分析

以具有层次结构的局域网作为拓扑模型,考虑共因失效和关联失效这2类节点非独立失效事件发生的情况,建立了交换机节点失效模型来模拟交换机失效,利用Monte-Carlo仿真算法近似计算出网络的两端可靠性,研究2种共因失效事件和3种关联失效事件对网络端端可靠性的影响。结果表明:因资源节点出现故障和协议层出现错误而导致交换机失效的共因失效事件均会降低网络可靠性,且资源节点失效概率或协议层失效概率越大,网络可靠性越低;而由于使用了热备份技术、堆叠技术以及发生广播风暴导致的关联失效事件,即使节点独立失效概率很小,只要相关因数足够大,故障都会快速传播,导致网络可靠性迅速下降。     

基于Monte Carlo的军事物流结点可靠性评估方法

军事物流网络结点是构成军事物流网络的基本要素。战场环境瞬息万变,结点的可靠性往往受许多不确定因素的影响,计及不确定因素的评估方法可以更客观、真实地评估结点的可靠性。基于此,提出了刻画物流结点可靠性的评估指标体系,建立了计及不确定因素的军事物流结点可靠性评估模型,给出了Monte Carlo求解算法。对影响结点可靠性的因素进行了分析,在此基础上提出了改善军事物流结点可靠性的措施。以某战役级军事物流网络为例进行算例分析,验证了该方法的可行性和正确性。     

作战飞机可靠性与维修性仿真模型

通过故障树分析建立了作战飞机仿真逻辑关系。在修正线性同余法的基础上获得了随机数模型。在各设备故障发生状态和修复状态识别的基础上,建立了可靠性维修性仿真模型,确定了作战飞机在仿真过程中的工作状态,并根据故障模式影响分析预计了设备故障对作战飞机的影响。最后以F/A-18为例进行可靠性维修性仿真,获得了实时的故障信息和修复信息,验证了仿真模型的可行性。     

液体火箭发动机无失效条件下的可靠性分析方法

针对液体火箭发动机热试车过程中可能出现的无失效情况,在对寿命分布进行分析的基础上,利用配分布曲线-最小二乘法,采用经典估计和Bayes估计作为先验分布,对液体火箭发动机无失效条件下的可靠性进行了评估,并对评估结果进行了分析。计算结果表明,采用最小二乘法结合Bayes估计,可以较好评估液体火箭发动机在无失效条件下的可靠性。     

火灾事故与民事侵权责任研究

火灾事故会给受害人造成人身和财产损失,存在民事责任。探讨了火灾事故民事侵权责任,从法律的角度论述了火灾事故民事侵权责任的追究和赔偿,并从建立和完善损害赔偿专家证人制度及火灾保险制度提出了完善火灾民事赔偿制度的建议。     

The logistic–exponential survival distribution

For various parameter combinations, the logistic–exponential survival distribution belongs to four common classes of survival distributions: increasing failure rate, decreasing failure rate, bathtub‐shaped failure rate, and upside‐down bathtub‐shaped failure rate. Graphical comparison of this new distribution with other common survival distributions is seen in a plot of the skewness versus the coefficient of variation. The distribution can be used as a survival model or as a device to determine the distribution class from which a particular data set is drawn. As the three‐parameter version is less mathematically tractable, our major results concern the two‐parameter version. Boundaries for the maximum likelihood estimators of the parameters are derived in this article. Also, a fixed‐point method to find the maximum likelihood estimators for complete and censored data sets has been developed. The two‐parameter and the three‐parameter versions of the logistic–exponential distribution are applied to two real‐life data sets. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Network reliability assessment in a random environment

In this paper we consider networks that consist of components operating under a randomly changing common environment. Our work is motivated by power system networks that are subject to fluctuating weather conditions over time that affect the performance of the network. We develop a general setup for any network that is subject to such environment and present results for network reliability assessment under two repair scenarios. We also present Bayesian analysis of network failure data and illustrate how reliability predictions can be obtained for the network. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 574–591, 2003     

弹药储存可靠性设计对策研究

从我军弹药储存可靠性设计现状出发，在深入分析某型弹药失效机理基础上，总结出了我军弹药产品储存性方面存在的质量问题；提出了弹药全系统相容的研究理念和储存性设计中的复合防护设计概念，并对如何提高弹药储存性能提出了建议。     

Two‐stage component test plans for testing the reliability of a series system

A system reliability is often evaluated by individual tests of components that constitute the system. These component test plans have advantages over complete system based tests in terms of time and cost. In this paper, we consider the series system with n components, where the lifetime of the i‐th component follows exponential distribution with parameter λ_i. Assuming test costs for the components are different, we develop an efficient algorithm to design a two‐stage component test plan that satisfies the usual probability requirements on the system reliability and in addition minimizes the maximum expected cost. For the case of prior information in the form of upper bounds on λ_i's, we use the genetic algorithm to solve the associated optimization problems which are otherwise difficult to solve using mathematical programming techniques. The two‐stage component test plans are cost effective compared to single‐stage plans developed by Rajgopal and Mazumdar. We demonstrate through several numerical examples that our approach has the potential to reduce the overall testing costs significantly. © 2002 John Wiley & Sons, Inc. Naval Research Logistics, 49: 95–116, 2002; DOI 10.1002/nav.1051