灰色关联投影法的威胁排序算法

威胁评估与排序是作战系统和C4I系统必须具备的重要功能.结合多指标决策理论和灰色系统理论,提出了基于多指标决策灰色关联投影法的威胁排序算法.首先通过建立灰色关联判断矩阵将威胁排序转化为多指标决策问题;其次为缩小极端值的影响提出了基于信息熵的威胁指标权重算法;最后从矢量投影角度应用灰色关联投影值进行威胁排序;并分别研究了分辨系数和指标权重对威胁排序的影响.通过现代防空作战实例验证了算法的有效性和工程实用性.     

解析方法与数值模拟相结合求解炸药在容器内部爆炸产生的壁面载荷

本文采用总变差递减（TVD）数值方法与强爆炸解析解相结合的手段,求解了炸药在爆炸容器内部产生的作用载荷。计算结果与实验值在几个典型位置进行了比较,二者有良好的符合。与单纯的数值方法相比,本文所探索的方法能有效地克服对称轴附近的数值振荡,不失为确定爆炸载荷的一种新途径。     

舰船最优概念设计方案的构造方法研究

在舰船概念设计阶段,设计者往往需要从大量设计方案中筛选优秀方案,此问题属于多属性多目标优化的问题,而进化算法的兴起为此类问题的解决提供了较好的途径.针对进化算法中Pareto最优解集的特点,结合舰船设计实际,提出一种新的构造最优解集的方法--提取法.案例验证表明,提取法是合理和有效的.     

近年来军事法学若干基础理论问题研究述论

军事法学基础理论研究水平的高低,直接反映了这一学科理论创新发展的程度.基础理论研究的不断深化,有助于促进学科理论体系趋于成熟和完善.近年来,军事法学基础理论研究不断深入发展,在诸多方面取得了重要研究成果.军事法学研究者围绕军事法的概念与调整范围、军事法的独立部门法地位、军事权、军事法体系以及军事法学研究方法等学科基础问题进行了富有成效的创新研究,有力提升了军事法学理论研究的学术水准,将军事法学研究推进到新的发展阶段.     

飞机系统安全性指标的Petri Net分配方法

为解决动态故障树抽象而不利于交流的问题,利用Petri Net直观、易用且适用范围广的优点,提出基于Petri Net的飞机系统安全性指标分配方法。通过整理安全性指标及其相关的可靠性指标,选取失效率作为安全性指标,对比动态故障树及Petri Net建模方法,选取后者建立静态逻辑变迁和动态逻辑变迁的Petri Net指标分配模型。在此基础上,提出考虑严酷等级的系统安全性指标分配方法,经过算例分析,构建Petri Net层次系统故障模型进行指标分配。结果表明,分配值均在相应安全性指标内,该方法能够克服动态故障树法不直观、等分配法分配过于粗糙等缺陷,为飞机安全性设计与评估提供参考。     

复合固体推进剂颗粒填充模型及其统计特性分析

复合固体推进剂属于高填充比颗粒类复合材料,氧化剂和金属颗粒在基体中的随机分布使其在细观尺度具有非均质的特点.从细观尺度研究固体推进剂燃烧及力学性能时,必须考虑颗粒级配、空间分布和种类等因素的影响.采用分子动力学方法,以硝酸酯增塑聚醚高能复合固体推进剂为研究对象,将固体颗粒模型化为球形,生成其在基体内随机分布的颗粒填充模...     

Round robin using the depth of penetration test method on an armour grade alumina

The depth of penetration (DOP) method is a well-known ballistic test method for characterisation and ranking of ceramic armour materials. The ceramic tile is bonded to a backing material of semi-infinite thickness, and the penetration depth of the projectile gives a measure of the performance of the ceramic. There is, however, an inherent variability in the results from this test method. In this work, the accuracy and the variability of the DOP method has been investigated in a round robin exercise. Six ballistic test centres took part in the exercise. A test protocol was developed, in which the threat type (projectile and impact conditions) and a procedure on how to prepare the targets were specified. The targets consisted of alumina tiles of two different thicknesses that were bonded to polycarbonate backing cubes. Two different 7.62 mm armour piercing projectiles were employed; one with a hard steel core and one with a tungsten carbide core. The projectiles and the other materials all came from single material batches in order to avoid batch-to-batch variations in material properties. These materials were distributed between the ballistic test centres. The test results of the different ballistic test facilities were collected and compared. There was not a lot of variation between the average DOP values obtained at each laboratory, but the variation in penetration depth between shots was high. The consequence of this variation may be less confidence in the test results, and a statistical method was used to evaluate the required number of tests that are sufficient to obtain an average result with high confidence. In most cases, the required number of tests is much higher than what is practically feasible. This work was conducted as part of the European Defence Agency-project CERAMBALL.     

火灾安全评价方法研究

火灾安全评价是利用系统工程的方法对拟建或已有工程、系统可能存在的危险性及可能产生的后果进行综合评价和预测,并根据可能导致的火灾事故风险的大小,提出相应的安全对策措施,以达到工程、系统安全的过程。主要论述了火灾安全评价的目的、火灾安全评价的意义、火灾安全评价的一般程序、火灾安全评价方法选择、火灾安全评价方法的比较及火灾安全评价方法在消防中应用。     

多脉冲导弹可达域优化方法设计与分析

为了更合理地制定导弹的战术指标和作战任务规划,对多脉冲导弹可达域进行研究。通过引入加权的纵程和横程的组合性能指标函数,将可达域的优化问题转化为最优控制问题,建立以飞行攻角和侧滑角为双优化设计变量的多阶段多约束优化模型,采用hp自适应伪谱法对其进行求解,并着重分析多脉冲导弹发动机参数和终端约束条件对导弹可达域的影响。仿真结果表明,hp自适应伪谱法能有效解决多阶段多约束的多脉冲导弹可达域优化问题,且多脉冲导弹脉冲发动机时间间隔越小,推力比越大,装药比越小,导弹的可达域越大,相比于终端速度对可达域的影响,终端弹道倾角对可达区域的影响较小。     

Annealing adaptive search,cross‐entropy,and stochastic approximation in global optimization

The Annealing Adaptive Search (AAS) algorithm for global optimization searches the solution space by sampling from a sequence of Boltzmann distributions. For a class of optimization problems, it has been shown that the complexity of AAS increases at most linearly in the problem dimension. However, despite its desirable property, sampling from a Boltzmann distribution at each iteration of the algorithm remains a practical challenge. Prior work to address this issue has focused on embedding Markov chain‐based sampling techniques within the AAS framework. In this article, based on ideas from the recent Cross‐Entropy method and Model Reference Adaptive Search, we propose an algorithm, called Model‐based Annealing Random Search (MARS), that complements prior work by sampling solutions from a sequence of surrogate distributions that iteratively approximate the target Boltzmann distributions. We establish a novel connection between MARS and the well‐known Stochastic Approximation method. By exploiting this connection, we prove the global convergence of MARS and characterize its asymptotic convergence rate behavior. Our empirical results indicate promising performance of the algorithm in comparison with some of the existing methods. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011