基于随机有限集理论的多传感器目标联合检测跟踪算法

针对杂波环境中的目标检测跟踪问题,提出一种基于随机有限集理论的多传感器目标联合检测跟踪算法。算法将目标状态和量测描述为随机集合,建立考虑目标出现、目标保持、目标消失等情况的目标状态随机有限集模型,以及考虑漏检和虚警的多传感器量测随机有限集模型。将目标的联合检测跟踪问题构建为目标状态集合的贝叶斯最优估计问题,并基于随机有限集理论对该贝叶斯估计算法的递推表达式进行严格理论推导。采用序贯蒙特卡罗技术实现算法的递推滤波。仿真结果验证了该算法的有效性以及算法相对于传统基于数据关联算法的性能优势。     

应力-强度模型的Bayes可靠性分析

当应力、强度分别服从于正态分布、指数分布和Weibull分布时 ,分析了应力 -强度模型的可靠性评估 ,着重讨论了无信息验前下的Bayes可靠性评估。仿真结果表明 ,无信息验前下的评估结论可以很好地用频率学派的观点来解释。     

广生灭过程的积分型随机泛函

讨论了广生灭过程的积分型随机泛函的概率分布，给出了分布的拉氏变换所满足的差分方程，且求出了它们的解     

伞盘结构对大长径比发动机药柱结构完整性的影响

为了提高大长径比发动机药柱结构完整性水平,基于三维黏弹性有限元法,计算某大长径比固体发动机在温度和内压荷载联合作用下的结构响应;研究伞盘结构及其位置对药柱最大Von Mises应变的影响规律;讨论当伞盘位于药柱中部时,伞盘最大Von Mises应变随伞盘宽度、深度以及顶部圆弧半径比的变化规律。结果表明,伞盘位于药柱中部时可以有效地降低大长径比药柱的最大Von Mises应变,增加伞盘宽度、深度或选取合适的半径比均可降低伞盘结构的最大Von Mises应变。所得结论可为固体发动机设计提供参考。     

采用随机矩阵理论的水声阵列SMI-MVDR空间谱估计技术

对角加载MVDR技术是一种经典的空间谱估计技术,在水声阵列信号处理中有着广泛的应用。该技术之所以具有较好的性能是由于其通过对角加载使样本协方差矩阵的特征值分散度减小。提出了基于随机矩阵理论的MVDR空间谱估计技术,具体思路是利用随机矩阵特征值的极限性质实现样本协方差矩阵噪声的抑制,以达到类似对角加载能够实现的特征值分散度减小的效果。仿真表明所提出的方法与对角加载方法达到了同样的目的,且当快拍数一定,而信噪比由小变大时,该方法可以达到与对角加载MVDR技术相当的性能;当信噪比设为定值,快拍数由小变大时,其与对角加载技术具有相同的DOA估计成功概率变化趋势,且在小样本情况下,此方法优势较为明显。     

电磁轨道炮轨道温度场与热应力数值仿真

在电磁轨道炮发射过程中,因热量累积而引起的急速温升与热应力对轨道性能和寿命有着重要的影响。为获得发射过程中轨道温度场及热应力分布情况,在分析轨道热载荷的基础上,建立了热载荷计算模型,并在给定的参数下,利用有限元仿真软件ANSYS Workbench对3种典型截面轨道的温度场与热应力进行了数值仿真。仿真结果表明:轨道温度场与热应力轴向上呈梯度分布,纵向上只扩散到内表面很薄的区域,温度与热应力最大值在电枢初始位置处;相较于矩形与凹形截面轨道,凸形截面轨道温升与热应力较低,性能较好。     

Inventory competition with yield reliability improvement

This article studies the inventory competition under yield uncertainty. Two firms with random yield compete for substitutable demand: If one firm suffers a stockout, which can be caused by yield failure, its unsatisfied customers may switch to its competitor. We first study the case in which two competing firms decide order quantities based on the exogenous reliability levels. The results from the traditional inventory competition are generalized to the case with yield uncertainty and we find that quantity and reliability can be complementary instruments in the competition. Furthermore, we allow the firms to endogenously improve their yield reliability before competing in quantity. We show that the reliability game is submodular under some assumptions. The results indicate that the competition in quantity can discourage the reliability improvement. With an extensive numerical study, we also demonstrate the robustness of our analytical results in more general settings. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 107–126, 2015     

利用验前信息的一种序贯检验方法——序贯验后加权检验方法

序贯验后加权检验方法是Bayes 统计观点在假设检验中的运用。本文提出了该方法的一般理论,给出了当总体的分布参数具有验前信息时的序贯检验方法。文中确定了决策区的划分,同时讨论了序贯截尾方案,给出了检验中可能犯两类错误的概率的上界,并将一般理论应用于产品的可靠性检验和再入飞行器随机落点的精度鉴定。由于运用了验前信息,因此能有效地在少量试验之下进行统计假设检验。本文所提供的方法对于昂贵产品试验结果的统计评定具有普遍意义。     

钢筋混凝土外粘钢板结构裂缝的有限元数值模拟

随着高技术武器的不断发展,防护工程正面临着前所未有的威胁和挑战,新型防护结构及材料已经成为研究的热点。针对这一实际背景,运用ANSYS大型有限元软件,采用数值模拟的方法对普通钢筋混凝土结构和外粘钢板混凝土结构在相同均布面荷载作用下的变形、钢筋应力以及结构裂缝的开展情况进行了比较。结果表明外粘钢板的钢筋混凝土结构能够大大增强结构的抗力,并且有效的抑制了裂缝的开展。     

Stochastic production capacity: A bane or a boon for quick response supply chains?

The quick response (QR) system that can cope with demand volatility by shortening lead time has been well studied in the literature. Much of the existing literature assumes implicitly or explicitly that the manufacturers under QR can always meet the demand because the production capacity is always sufficient. However, when the order comes with a short lead time under QR, availability of the manufacturer's production capacity is not guaranteed. This motivates us to explore QR in supply chains with stochastic production capacity. Specifically, we study QR in a two-echelon supply chain with Bayesian demand information updating. We consider the situation where the manufacturer's production capacity under QR is uncertain. We first explore how stochastic production capacity affects supply chain decisions and QR implementation. We then incorporate the manufacturer's ability to expand capacity into the model. We explore how the manufacturer determines the optimal capacity expansion decision, and the value of such an ability to the supply chain and its agents. Finally, we extend the model to the two-stage two-ordering case and derive the optimal ordering policy by dynamic programming. We compare the single-ordering and two-ordering cases to generate additional managerial insights about how ordering flexibility affects QR when production capacity is stochastic. We also explore the transparent supply chain and find that our main results still hold.