基于SLAM的图形建模仿真环境

本文详细介绍了基于ＳＬＡＭ的图形建模仿真环境的设计与应用，包括图形建模环境的实现，ＳＬＡＭ网络的进程交互仿真策略以及仿真器的设计，并进一步探讨了该系统用于协同仿真进行混合异构建模的思想。     

基于微裂纹模型的材料可靠性预计

讨论了微裂纹的某些不同于大型裂纹的增长特性,提出了一种微裂纹在某种材料上的多级扩展模型,利用微裂纹的增长数据来预计材料的可靠性。     

软件可靠性数学仿真测试平台设计与研制

针对火控软件的特点和要求,研制出面向软件可靠性验证的数学仿真测试平台,并根据典型的火控程序,有效地完成了分析与测试工作.测试系统界面友好,测试结果达到设计要求.     

战车火控系统软件可靠性的仿真测试平台

以平均无故障时间间隔(MTBF)和任务成功率为主指标,以某型坦克火控系统为载体,提出了战车非制导武器火控系统软件可靠性仿真测试平台的方案,并对其软件可靠性的仿真测试与验证技术进行了讨论.     

装备系统保障性的界定探讨

本文通过对武器装备的保障、保障性的定义与内涵、保障性参数、保障性与可靠性以及维修性的界面处理等问题的研究,探讨装备系统保障性的界定问题.     

一种多通道武器控制台的可靠性预计分析

对设计的一种多通道武器控制台的可靠性进行了预估分析.采用元器件计数法和元器件应力分析法,得出了模块级的失效率.按照系统串联结构的可靠性框图,计算出系统的失效率、平均无故障工作时间等可靠性指标.结果表明,预计值满足了系统规定的使用要求.     

Attrition models of the Ardennes campaign

This paper revisits the modeling by Bracken [3] of the Ardennes campaign of World War II using the Lanchester equations. It revises and extends that analysis in a number of ways: (1) It more accurately fits the model parameters using linear regression; (2) it considers the data from the entire campaign; and (3) it adds in air sortie data. In contrast to previous results, it concludes by showing that neither the Lanchester linear or Lanchester square laws fit the data. A new form of the Lanchester equations emerges with a physical interpretation. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 1–22, 1998     

超高斯随机振动环境的疲劳强化机理

针对可靠性强化试验的全轴随机振动环境的超高斯幅值分布特性开展其疲劳强化机理研究。首先通过理论分析表明RS机振动激励下试件应力仍保持超高斯分布,然后证明了同等量级下的超高斯分布比高斯分布随机应力具有更高的疲劳强化效能,从而揭示RS机全轴随机振动环境超高斯幅值分布特性的疲劳强化机理。     

可靠度限制下相控阵雷达天线阵面T/R单元维修模型

为了描述维修活动对相控阵雷达天线阵面系统的影响,构建了以可靠度为基础的“修旧不如新”定期维修优化模型。对相控阵雷达T/R单元失效下的天线性能参数进行分析,根据指标确定系统不能正常工作的失效T/R单元阈值; 针对大部分维修活动都难以使T/R单元修复如新的事实,引入失效率递增因子,在系统一定的可靠度水平上,以相控阵雷达系统的使用可用度和维修费用率为优化决策参数,建立了系统的维修优化模型,并运用边际效能算法对系统的最佳预防换件维修周期和换件维修组数量进行求解。实例运算结果表明,该模型突破了已有模型“修旧如新”的限制条件,更符合实际,能为维修策略的制定提供理论依据。     

Pairwise model discrimination with applications in lifetime distributions and degradation processes

Reliability data obtained from life tests and degradation tests have been extensively used for purposes such as estimating product reliability and predicting warranty costs. When there is more than one candidate model, an important task is to discriminate between the models. In the literature, the model discrimination was often treated as a hypothesis test and a pairwise model discrimination procedure was carried out. Because the null distribution of the test statistic is unavailable in most cases, the large sample approximation and the bootstrap were frequently used to find the acceptance region of the test. Although these two methods are asymptotically accurate, their performance in terms of size and power is not satisfactory in small sample size. To enhance the small‐sample performance, we propose a new method to approximate the null distribution, which builds on the idea of generalized pivots. Conventionally, the generalized pivots were often used for interval estimation of a certain parameter or function of parameters in presence of nuisance parameters. In this study, we further extend the idea of generalized pivots to find the acceptance region of the model discrimination test. Through extensive simulations, we show that the proposed method performs better than the existing methods in discriminating between two lifetime distributions or two degradation models over a wide range of sample sizes. Two real examples are used to illustrate the proposed methods.