Blast resistance evaluation of urban utility tunnel reinforced with BFRP bars

To improve corrosion-resistance of shallow-buried concrete urban utility tunnels(UUTs),basalt fiber reinforced polymer(BFRP)bars are applied to reinforce UUTs.As the UUT must have excellent survival capability under accidental explosions,a shallow-buried BFRP bars reinforced UUT(BBRU)was designed and constructed.Repetitive blast experiments were carried out on this BBRU.Dynamic responses,damage evolutions and failure styles of the BBRU under repetitive explosions were revealed.The tunnel roof is the most vulnerable component and longitudinal cracks develop along the tunnel.When the scaled distance is larger than 1.10 m/kg1/3,no cracks are observed in the experiments.When the BBRU is severely damaged,there are five cracks forming and developing along the roof.The roof is simplified as a clamped-supported one-way slab,proved by the observation that the maximum strain of the transverse bar is much larger than that of the longitudinal bar.Dynamic responses of the roof slab are predicted by dynamic Euler beam theory,which can consistently predict the roof displacement under large-scaled-distance explosion.Compared with the UUT reinforced with steel bars,the BBRU has advantages in blast resistance with smaller deflections and more evenly-distributed cracks when the scaled distance is smaller than 1.260 m/kg1/3 and the steel bars enter plastic state.Longer elastic defamation of the BFRP bars endows the UUT more excellent blast resistance under small-scaled-distance explosions.     

对流层散射无源监视系统最优布局方法

为提高对流层散射无源监视系统对辐射源的定位精度,利用改进粒子群优化算法对分布式监视节点进行最优布局设计。推导了基于电磁波方位到达角定位机制下的几何精度因子。在改进粒子群优化算法中,采用混沌理论初始化所有粒子的初始参数;通过自适应变化的惯性权重和学习因子来提高算法寻优能力;为防止粒子陷入局部最优,利用双子群机制进行寻优,并在两子群之间进行交叉变异操作,以增加粒子的多样性。仿真结果表明:相对于几种常规的布站方式,所提算法能够明显提高监视系统对辐射源的定位精度,运行时间较遍历寻优算法有所减少。     

基于AKF的AUV对接回收组合导航研究

针对自主水下机器人(Autonomous Underwater Vehicle,AUV)在回收过程中的组合导航精度问题,提出了一种改进的高斯距离迭代法及改进的自适应卡尔曼滤波算法(Adaptive Kalman Filter,AKF).基于AUV回收对接系统,研究并建立了针对惯导SINS、超短基线USBL、多普勒计程仪DVL和深度计的基于斜距的组合导航模型.通过对SINS/USBL/DVL/深度计组合导航量测信息误差特性分析,设计了改进的基于斜距的SINS/USBL/DVL/深度计组合导航模型;针对该模型突出的滤波发散问题,设计了基于滤波收敛性判据和强跟踪滤波思想改进的AKF滤波算法进行有机融合.仿真结果表明,此研究使实际AUV系统具有更高的滤波精度和可靠性.     

改进的YOLOV3算法在小目标检测中的研究与应用

战场目标的图像检测与识别对于战场监视、侦察、毁伤状态评估和火控系统研究等具有重要作用.以坦克装甲目标为研究对象,选用识别精度高、速度快的YOLOV3为基础目标检测模型,针对复杂战场环境中获取图像目标特征信息少的问题,引入多尺度特征增强结构的方法对YOLOV3模型进行改进,通过丰富特征图多样性的方式,提高模型性能.在坦克数据集上的实验结果表明,改进后的算法对于复杂战场环境下的小目标特征具有更强的敏感性,较大程度上增强了模型的识别精度.     

Becoming a disarmament champion: the Austrian crusade against nuclear weapons

ABSTRACT

The making of the Treaty on the Prohibition of Nuclear Weapons (TPNW) has put Austria and its involvement in nuclear disarmament in the spotlight. This study highlights several factors that led Austria to become a prominent voice in nuclear-disarmament debates. First, its involvement dovetails with the emphasis on humanitarian disarmament it has promoted since the 1990s. Second, a strong antinuclear identity pervades Austrian society. This “nuclear allergy” combines antimilitarism inherited from the Cold War and, more broadly, an aversion to nuclear power, including for energy purposes. These two considerations form the background to the increased activism of the Austrian Foreign Ministry on nuclear disarmament in international fora. But, equally, Austria’s crusade for the TPNW can be attributed to the engagement of a small team of diplomats implementing personal as well as national preferences in favor of disarmament.