Multi-objective design optimization of composite submerged cylindrical pressure hull for minimum buoyancy and maximum buckling load capacity

This paper presents the design optimization of composite submersible cylindrical pressure hull subjected to 3 MPa hydrostatic pressure. The design optimization study is conducted for cross-ply layups [0s/90t/0u], [0s/90t/0u]s, [0s/90t]s and [90s/0t]s considering three uni-directional composites, i.e. Carbon/Epoxy, Glass/Epoxy, and Boron/Epoxy. The optimization study is performed by coupling a Multi-Objective Genetic Algorithm (MOGA) and Analytical Analysis. Minimizing the buoyancy factor and maximizing the buckling load factor are considered as the objectives of the optimization study. The objectives of the optimization are achieved under constraints on the Tsai-Wu, Tsai-Hill and Maximum Stress composite failure criteria and on buckling load factor. To verify the optimization approach, optimization of one particular layup configuration is also conducted in ANSYS with the same objectives and constraints.     

Replicated batch means for steady‐state simulations

This paper studies a new steady‐state simulation output analysis method called replicated batch means in which a small number of replications are conducted and the observations in these replications are grouped into batches. This paper also introduces and compares methods for selecting the initial state of each replication. More specifically, we show that confidence intervals constructed by the replicated batch means method are valid for large batch sizes and derive expressions for the expected values and variances of the steady‐state mean and variance estimators for stationary processes and large sample sizes. We then use these expressions, analytical examples, and numerical experiments to compare the replicated batch means method with the standard batch means and multiple replications methods. The numerical results, which are obtained from an AR(1) process and a small, nearly‐decomposable Markov chain, show that the multiple replications method often gives confidence intervals with poorer coverage than the standard and replicated batch means methods and that the replicated batch means method, implemented with good choices of initialization method and number of replications, provides confidence interval coverages that range from being comparable with to being noticeably better than coverages obtained by the standard batch means method. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

统计模型在火灾统计中的应用

通过分析已有的火灾统计数据,建立了简单的二元线性回归模型,并对此模型进行了显著性检验。分析表明违规操作和电气故障是群死群伤火灾的主要因素。可以利用此模型分析火灾统计中不同形式的数据,并进一步说明统计模型在火灾统计中的作用。     

近程反导中拦阻射击模式和多重命中体制研究

在近程反导中,片面强调提高高炮随动系统的跟踪瞄准速度,已经不现实,通过对拦阻射击模式的研究,探讨了采用多重命中体制弥补随动系统缺陷的可行性。     

A stochastic model for burn‐in procedures in accelerated environment

Burn‐in procedure is a manufacturing technique that is intended to eliminate early failures of system or product. Burning‐in a component or system means to subject it to a period of use prior to being used in field. Generally, burn‐in is considered expensive and so the length of burn‐in is typically limited. Thus, burn‐in is most often accomplished in an accelerated environment in order to shorten the burn‐in process. A new failure rate model for an accelerated burn‐in procedure, which incorporates the accelerated ageing process induced by the accelerated environmental stress, is proposed. Under a more general assumption on the shape of failure rate function of products, which includes the traditional bathtub‐shaped failure rate function as a special case, upper bounds for optimal burn‐in time will be derived. A numerical example will also be given for illustration. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

新型多目标遗传算法及其在导弹射击效能优化中的应用

多目标规划是一类重要的优化模型,有着广泛的实际应用,但其求解至今仍是运筹学的一个难点.针对一般约束多目标优化问题,在设计了新的适应度函数和选择算子的基础上,提出一种新型多目标遗传算法.将其应用于导弹对集群目标射击效能优化问题,验证了算法的有效性.     

CS模型下IMM-PF算法在机动目标跟踪中的应用

为了解决机动目标定位跟踪问题,提出了一种基于CS(current statistical)模型的交互式多模型粒子滤波算法.在交互式多模型粒子滤波算法的基础上,计算CS模型的概率,自适应地调整CS模型中的目标加速度,反映出了目标的机动特性,充分发挥2种算法的优点,改善了CS模型的加速度不能自适应调整的缺点,提高了CS模型的自适应性和应用范围.另外,CS模型的自适应滤波方法由Kalman滤波改为粒子滤波.通过Monte Carlo对比仿真试验表明了该算法的可行性和优越性.     

色噪声环境下MIMO雷达相干目标角度估计算法

针对色噪声环境下的MIMO雷达相干目标角度估计问题,提出一种基于目标信息矢量重构的角度估计算法.算法对MIMO雷达的接收数据进行了低复杂度改进,通过计算四阶累积量,得到一组矢量并证明该矢量包含所有目标的角度信息,通过重构Toeplitz矩阵,结合MUSIC算法实现了色噪声环境下MIMO雷达相干目标的角度估计.算法保留了MIMO雷达的阵元扩展能力和目标分辨力,具有自动抑制加性高斯白噪声和色噪声的能力,实现了相干目标的有效估计,更利于在实际中应用.最后计算机仿真结果证实了算法的有效性和可行性.     

地球静止轨道卫星系统兼容性多维度分析方法

针对地球静止轨道(Geostationary Satellite Orbit, GSO)卫星系统间的兼容性分析,设计了单波束和多波束GSO卫星系统间的上行及下行干扰场景,并在卫星的轨位、系统链路可用度及干扰系统地球站选址等多维度对GSO卫星系统间的干扰进行了评估,提出了不同轨位间隔条件下满足国际电信联盟干扰协调限值的干扰系统地球站最近选址的建议,细化了各维度研究上的颗粒度,在不同维度间进行横向对比,分析了GSO卫星系统在不同维度下的干扰变化特性曲线和各维度对干扰分析结果的影响程度。在系统链路可用度一定的条件下,两个卫星系统的轨位间隔>2°时,干扰数值变化缓慢;轨位间隔≤2°时,干扰数值变化较快;轨位间隔≤0.1°时,干扰数值急剧上升。以国际电信联盟实际登记的CHNSAT-81.5和INSAT-KA82.5E卫星的网络资料为例,将计算得到的GSO系统波束间的干扰噪声比、载波干扰比与Visualyse软件结果进行验证对比,结果误差保持在0.7 dB范围内,证明该方法具有有效的评估性能。     

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。