Transient analysis of Markov models of fault‐tolerant systems with deferred repair using split regenerative randomization

The (standard) randomization method is an attractive alternative for the transient analysis of continuous time Markov models. The main advantages of the method are numerical stability, well‐controlled computation error, and ability to specify the computation error in advance. However, the fact that the method can be computationally very expensive limits its applicability. In this paper, we develop a new method called split regenerative randomization, which, having the same good properties as standard randomization, can be significantly more efficient. The method covers reliability‐like models with a particular but quite general structure and requires the selection of a subset of states and a regenerative state satisfying some conditions. For a class of continuous time Markov models, model class C₂, including typical failure/repair reliability‐like models with exponential failure and repair time distributions and deferred repair, natural selections are available for both the subset of states and the regenerative state and, for those natural selections, theoretical results are available assessing the efficiency of the method in terms of “visible” model characteristics. Those results can be used to anticipate when the method can be expected to be competitive. We illustrate the application of the method using a large class C₂ model and show that for models in that class the method can indeed be significantly more efficient than previously available randomization‐based methods. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

架构和模式在水声信息流仿真软件中的应用

水声信息流仿真软件系统涉及多目标、多声纳以及多变的海洋环境.仿真软件的复用性是现代软件工程的重要性能指标.针对系统开放性的特点,在领域分析模型的基础上,采用了面向对象方法设计仿真软件模型.为了满足软件多层次复用的需求,应用软件架构技术和设计模式设计仿真软件.根据水声信息流仿真软件需求,系统划分为四层结构;按功能,层又可分解为包.可复用的设计模式用于设计不同层和包中类之间的关系.提出的仿真软件模型具有良好的可扩充性与可复用性.     

模糊推理在软件维护性评估和预测中的应用

摘要：在基于活动的质量模型维护性分析方法基础上,对贝叶斯方法进行了扩展,将模糊推理技术与现有的贝叶斯方法进行比较,开发了一个基于模糊推理的系统来对软件维护性进行量化评估和预测,描述了模糊技术在维护性评估和预测准确度方面的优势．     

Component importance for linear consecutive‐ k ‐Out‐of‐ n and m ‐Consecutive‐ k ‐Out‐of‐ n systems with exchangeable components

Measuring the relative importance of components in a mechanical system is useful for various purposes. In this article, we study Birnbaum and Barlow‐Proschan importance measures for two frequently studied system designs: linear consecutive k ‐out‐of‐ n and m ‐consecutive‐ k ‐out‐of‐ n systems. We obtain explicit expressions for the component importance measures for systems consisting of exchangeable components. We illustrate the results for a system whose components have a Lomax type lifetime distribution. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

Nonparametric bayesian lifetime data analysis using dirichlet process lognormal mixture model

We propose a nonparametric Bayesian lifetime data analysis method using the Dirichlet process mixture model with a lognormal kernel. A simulation‐based algorithm that implements the Gibbs sampling is developed to fit the Dirichlet process lognormal mixture (DPLNM) model using rightly censored failure time data. Five examples are used to illustrate the proposed method, and the DPLNM model is compared to the Dirichlet process Weibull mixture (DPWM) model. Results indicate that the DPLNM model is capable of estimating different lifetime distributions. The DPLNM model outperforms the DPWM model in all the examples, and the DPLNM model shows promising potential to be applied to analyze failure time data when an appropriate parametric model for the data cannot be specified. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

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ANSYS的油罐拱顶稳定性分析

针对加肋拱顶稳定性十分复杂的问题,基于ANSYS建立了加肋拱顶油罐的三维有限元模型,对加肋拱顶的结构稳定性进行了数值模拟。对加肋拱顶在外压作用下的线性与非线性临界屈曲载荷进行了对比分析,利用弧长法获得了拱顶在加肋情况下径向、环向、轴向的载荷-位移曲线。结果表明:数值模拟的加肋拱顶屈曲方向和屈曲区域与实际失稳结果相一致,可以为加肋拱顶设计和稳定性分析提供一定参考。     

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。